阅读说明：本技术 通信系统、控制设备、存储介质及资源分配方法 (Communication system, control device, storage medium, and resource allocation method ) 是由 朱旭 陈丽珍 蒋宇飞 于 2020-12-09 设计创作，主要内容包括：本申请涉及一种通信系统、控制设备、存储介质及资源分配方法,在主网络与次级网络中利用强信道次级用户充当中继节点,并将OFDMA技术、协作NOMA技术及认知无线电技术结合起来进行通信系统的频谱资源分配、用户配对及功率分配,提高了系统的频谱利用率,增加了接入用户的数量。(The application relates to a communication system, a control device, a storage medium and a resource allocation method, wherein a strong channel secondary user is used as a relay node in a main network and a secondary network, and an OFDMA (orthogonal frequency division multiple Access) technology, a cooperative NOMA (non-orthogonal frequency division multiple Access) technology and a cognitive radio technology are combined to allocate frequency spectrum resources, pair users and allocate power of the communication system, so that the frequency spectrum utilization rate of the system is improved, and the number of access users is increased.)

1. A method for resource allocation in a communication system, the communication system comprising: a primary network and a secondary network, the primary network comprising: the system comprises a main base station, a strong channel main user, a strong channel secondary user and a weak channel main user, wherein the secondary network comprises: a secondary base station, a strong channel secondary user and a weak channel secondary user, wherein the strong channel secondary user can be used as a relay node between the main base station and the weak channel main user in the main network, and can also be used as a relay node between the secondary base station and the weak channel secondary user in the secondary network, and the method comprises the following steps:

and (3) spectrum resource allocation: dividing frequency spectrum resources by using an Orthogonal Frequency Division Multiple Access (OFDMA) technology to obtain subcarrier blocks, allocating the subcarrier blocks to a primary user according to user channel gain sequencing under each subcarrier aiming at the primary network, and allocating the subcarrier blocks to a secondary user according to user channel gain sequencing under each subcarrier aiming at the secondary network;

user pairing: according to a spectrum resource allocation result, acquiring cooperative data rates of the strong channel secondary users and the weak channel primary users on corresponding subcarrier blocks for the main network, pairing the strong channel secondary users and the weak channel primary users according to the cooperative data rate sequence, acquiring cooperative data rates of the strong channel secondary users and the weak channel secondary users on the corresponding subcarrier blocks for the secondary network, and pairing the strong channel secondary users and the weak channel secondary users according to the cooperative data rate sequence;

power distribution: according to the spectrum resource allocation and user pairing results, based on the constructed system weighted spectrum efficiency optimization objective function, under the power constraint condition, the power allocation value is obtained, and power allocation is carried out according to the power allocation value.

2. The method of claim 1, wherein in spectrum resource allocation, if there are allocated and unallocated subcarrier blocks for the same primary/secondary user, user channel gains under the allocated and unallocated subcarrier blocks are compared, and subcarrier block reallocation is selected according to the comparison result.

3. The method according to claim 1, wherein in the user pairing, if there are allocated and unallocated strong channel secondary users for the same weak channel primary user/weak channel secondary user, the allocated and unallocated strong channel secondary users are compared with the cooperative data rates of the weak channel primary user/weak channel secondary user on the corresponding subcarrier blocks, respectively, and the reallocation of the strong channel secondary user is selected according to the comparison result.

4. The method of claim 1, wherein in power allocation, the system weighted spectral efficiency optimization objective function is transformed into a linear form using a taylor expansion, and a method of successive iterative convex approximation of a convex standard deviation DC and a CVX solver are applied to find power allocation values.

5. A control device of a communication system, characterized by comprising: a processor and a memory, the memory storing a computer program that can be invoked by the processor, the computer program, when invoked, performing the method of any of claims 1-4.

6. A communication system, comprising: the control device of claim 5.

7. A computer storage medium, characterized in that the computer storage medium stores a computer program that is invoked by a processor to perform the method according to any one of claims 1-4.

Technical Field

The present application relates to the field of communications technologies, and in particular, to a communication system, a control device, a storage medium, and a resource allocation method.

Background

With the development of artificial intelligence and the rise of some emerging industries, such as smart factories, smart homes, remote medical operations and the like, the requirements on communication quality are higher and higher, namely large-scale connection, low delay and the like. This requires more spectrum resources, which may be fixed. At present, the management mode of the spectrum resources is mainly a static allocation mode, that is, a fixed section of spectrum is authorized to be used exclusively by a department, and the department cannot necessarily fully use the section of spectrum resources, which results in low utilization rate of the spectrum resources.

The cognitive radio technology is that a Secondary User (SU) intelligently adjusts operating parameters of the Secondary User, and accesses a frequency spectrum occupied by a Primary User (PU) in an opportunistic or cooperative manner, i.e., SUs is allowed to operate on the frequency spectrum reserved for PUs, and meanwhile, the service quality of a Primary Network (PN) is maintained, so that unused frequency spectrum resources in the Primary Network are utilized by the Secondary User, and the number of access users and the frequency spectrum efficiency of a system are improved.

The Non-Orthogonal Multiple Access (NOMA) technology is different from the traditional Multiple Access technology, information of a plurality of users is superposed at a transmitting base station through different power distribution coefficients, then the power distributed by a strong user with good channel condition is small, and then a signal with large power can be sequentially detected through a Successive Interference Cancellation (SIC) technology, then the signal is removed, and then the information of the strong user is obtained through decoding. NOMA can achieve the challenging requirements of future mobile communication networks, such as high data rate, high spectrum efficiency, large-scale connection and low delay, NOMA can generate a data rate larger than that of Orthogonal Multiple Access (OMA) technology, and ensure that users obtain fair service; in the cooperative NOMA technology, a Strong channel User (Strong User) serves as a relay to serve a Weak channel User (Weak User, WU), so that the receiving reliability of the Weak channel User (WU) is improved.

The OFDMA technique divides the spectrum resources into a certain number of orthogonal and non-overlapping subcarrier blocks, and dynamically allocates the subcarrier blocks to users. In addition, since the subcarrier blocks used by the users are mutually overlapped and intersected, no interference exists among the users, namely no multiple access interference exists. The OFDMA technique thus not only improves system throughput and spectrum utilization, but also increases the number of users accessing.

However, few studies have been made in the prior art by combining OFDMA technology, cooperative NOMA technology, and cognitive radio technology.

Disclosure of Invention

The present application is directed to providing a solution to at least one of the above problems.

The application provides a resource allocation method of a communication system, wherein the communication system comprises the following steps: a primary network and a secondary network, the primary network comprising: the system comprises a main base station, a strong channel main user, a strong channel secondary user and a weak channel main user, wherein the secondary network comprises: a secondary base station, a strong channel secondary user and a weak channel secondary user, wherein the strong channel secondary user can be used as a relay node between the main base station and the weak channel main user in the main network, and can also be used as a relay node between the secondary base station and the weak channel secondary user in the secondary network, and the method comprises the following steps:

and (3) spectrum resource allocation: dividing frequency spectrum resources by using an Orthogonal Frequency Division Multiple Access (OFDMA) technology to obtain subcarrier blocks, allocating the subcarrier blocks to a primary user according to user channel gain sequencing under each subcarrier aiming at the primary network, and allocating the subcarrier blocks to a secondary user according to user channel gain sequencing under each subcarrier aiming at the secondary network;

user pairing: according to a spectrum resource allocation result, acquiring cooperative data rates of the strong channel secondary users and the weak channel primary users on corresponding subcarrier blocks for the main network, pairing the strong channel secondary users and the weak channel primary users according to the cooperative data rate sequence, acquiring cooperative data rates of the strong channel secondary users and the weak channel secondary users on the corresponding subcarrier blocks for the secondary network, and pairing the strong channel secondary users and the weak channel secondary users according to the cooperative data rate sequence;

power distribution: according to the spectrum resource allocation and user pairing results, based on the constructed system weighted spectrum efficiency optimization objective function, under the power constraint condition, the power allocation value is obtained, and power allocation is carried out according to the power allocation value.

The present application also provides a control device of a communication system, including: a processor and a memory, the memory storing a computer program for invocation by the processor, the computer program, when invoked, being executable to perform the method as described above.

The present application also provides a communication system, comprising: such as the control device described above.

The application also provides a computer storage medium, which stores a computer program, and the computer program is called by a processor to execute the method.

The beneficial effect of this application lies in:

by providing a communication system, a control device, a storage medium and a resource allocation method, a strong channel secondary user is used as a relay node in a main network and a secondary network, and an OFDMA (orthogonal frequency division multiple Access) technology, a cooperative NOMA (non-orthogonal frequency division multiple Access) technology and a cognitive radio technology are combined to perform spectrum resource allocation, user pairing and power allocation of the communication system, so that the spectrum utilization rate of the system is improved, and the number of access users is increased.

Drawings

Fig. 1 is a cognitive cooperative NOMA system model of a multi-carrier multi-user according to a first embodiment of the present application.

Fig. 2 is a schematic diagram of a change in system spectral efficiency with the number of SUs according to the first embodiment of the present application.

Fig. 3 is a schematic diagram of the system fairness performance varying with the number of SUs according to the first embodiment of the present application.

Fig. 4 is a schematic diagram illustrating a variation of the number of users that are effectively accessed to the system according to the first embodiment of the present application along with the numbers of SUs and PUs.

Fig. 5 is a schematic diagram of a change of a system spectral efficiency with a variance value of a channel estimation error according to a first embodiment of the present application.

Fig. 6 is a schematic diagram illustrating a change of system spectrum efficiency with the number of SUs and PUs according to a first embodiment of the present application.

Fig. 7 is a schematic diagram illustrating a variation of an average data rate of a system user with the number of SUs according to a first embodiment of the present application.

Fig. 8 is a schematic diagram illustrating the change of the spectral efficiency of the system with the weight coefficients of the SUs and the number of PUs according to the first embodiment of the present application.

Fig. 9 is a schematic diagram illustrating a change of a system utility value with the number of SUs according to the first embodiment of the present application.

Fig. 10 is a simulation diagram of a system utility function changing with a coefficient value according to a first embodiment of the present application.

Detailed Description

The principle of the invention according to the present application will be described in detail with reference to some embodiments, which are used for explaining the invention and do not represent that the scope of protection of the present application only includes the embodiments, and other embodiments not listed below and belonging to the inventive concept are still within the scope of protection of the present application.

The first embodiment is as follows:

the embodiment of the application provides a resource allocation method of a communication system. The method will be described in detail below in several sections.

In view of the above analysis, it is known that the spectrum utilization rate of the system can be improved and the number of access users can be increased by effectively combining the OFDMA technology, the cooperative NOMA technology, and the cognitive radio technology. To this end, the present study will develop a study on how to better integrate these three technologies together.

Based on the above openness problem, the cooperative transmission mechanism technology of cognitive cooperative NOMA network and the joint resource allocation technology of primary network and secondary network under multi-carrier will be studied herein.

(1) A novel Cooperative NOMA (C-NOMA) strategy is provided, wherein SU acts as a receiver and a relay between a transmitter and a weak user to assist the transmission of the information of the weak user, thereby improving the reachable rate of the weak user.

(2) The cooperative transmission mechanism and resource allocation of the multi-carrier multi-user cognitive cooperative NOMA network are deeply researched. Joint resource allocation is performed for a Primary Network (PN) and a Secondary Network (SN). Three transmission mechanisms are proposed based on this kind of network 1) a cooperative NOMA strategy is adopted only in the main network, and no processing is done for the remaining subcarriers and the secondary users; 2) only adopting a cooperative NOMA strategy in the main network, distributing the rest subcarriers to unmatched secondary users through a secondary base station under the condition of meeting the performance of a main user, and adopting an OMA strategy to transmit information; 3) and adopting a cooperative NOMA strategy in both the primary network and the secondary network, distributing the rest subcarriers to the unmatched SU through the secondary base station under the condition of meeting the performance of the primary user, and transmitting information by adopting an OMA or cooperative NOMA strategy. And constructs a function with spectral efficiency as an optimization objective. Due to the non-convexity of the objective function, a feasible user selection and power allocation scheme is proposed herein.

System model

As shown in fig. 1, the system model of the above-mentioned multi-carrier multi-user cognitive cooperation NOMA mainly includes a main base station (PT), four secondary base Stations (ST), K PUs, and J SUs. In the system, the time slot has a duration T, and the entire frequency band is divided into N orthogonal subcarriers. The corresponding communication channel link mainly considers the path loss and the Rayleigh fading, and the noise is additive white Gaussian noise. And without loss of generality, the bandwidth per subcarrier is denoted B_sAnd the total bandwidth is B. WhereinAndrespectively representing PU transmitted on sub-carrier i_k，And SU_jE is desired, rSU is a relay user su (relay Secondary user):

for the sake of clarity, we first briefly introduce the proposed mechanism of cognitively cooperative NOMA networks. Without loss of generality, it is assumed that primary user PU1 and primary user PU3 have good channel conditions, while primary user PU2 has poor channel quality due to its high path loss or deep channel fading. It is clear that the Primary base station (PT) serves PU1, SU1, PU3, which have good channel conditions on subcarriers 1,2, 3, respectively. The SU1 then relays the signal to the PU2, which has poor channel conditions. After meeting the requirements of all primary user PUs, the secondary base stations ST1 and ST2 serve SUs 2 and SU3 using unallocated subcarriers (uSC)4 and uSC5, respectively. Furthermore, ST4 serves SU4 over uSC 6. SU4 then forwards the signal to SU5 using uSC6 as a relay. The proposed C-NOMA scheme has two phases, where the user with better channel conditions (called strong user) acts as a relay and receiver assisting the weak PU in the primary network or the weak SU in the secondary network, respectively. The first stage is as follows: the transmitter transmits relay SU and weak user (weak PU/SU, wPU/wSU) signals to the relay rSU in a first time slot by C-NOMA, and the rSU decodes their signals. And a second stage: the rSU relays the signal to the weak user (PU or SU with poor reception reliability) in the second time slot.

(II) optimization problem construction

In this section, the construction of the transmission channel according to the system model will be studied and a corresponding solution will be formulated. The proposed win-win cooperative NOMA scheme is employed in both networks, i.e. the primary and secondary networks, to assist users with poor reception reliability in both networks as much as possible. For the cooperative NOMA strategy, the power domain NOMA strategy is adopted for superposition relay of information of a secondary user rSU and a weak user (wPU/wSU). And modeling analysis is performed for imperfect Channel State Information (CSI).

For the primary network, the primary base station uses multi-carrier, i.e. OFDMA, technology, which means that each sub-carrier can be assigned to signal to the primary user PU through OMA strategy or to signal to the relay rSU through C-NOMA strategy.

Specifically, for a given timeslot, if PUk e {1, 2.. multidata, K } is assigned a subcarrier i e {1, 2.. multidata, N } and the channel condition from the base station to it is good, then OMA transmission, PU, is used_kThe received signal of (a) may be expressed as:wherein the content of the first and second substances,

whereinIndicating a primary user PU from a primary base station PT_kGain of the communication channel on subcarrier i, andis the channel gainIs determined by the estimated value of (c),is the estimation error, is the varianceIndependent zero mean complex gaussian random variables independent of channel gainRepresents the power transmitted by the base station PT to the PU;indicating transmission of the main base station PT on subcarrier i to the PU_kThe signal of (a);PU represented on subcarrier i_kComplex white Gaussian noise, σ^kRepresenting the variance value of the noise received at the primary user PUk.

Then the corresponding PU on subcarrier i_kThe achievable rates are:

wherein the content of the first and second substances,

the estimation error is treated as noise due to imperfect channel estimation.

On the other hand, when the master base station PT transmits in the cooperative NOMA scheme, the relay rSU j_rE {1, 2.., J } and weak user PU k (wPU)_k) Signals are superimposed and transmitted from the PT by the C-NOMA scheme. In the first stage, on subcarrier iThe received signals are:

wherein the content of the first and second substances,

whereinIndicating the secondary user from the primary base station PT to the relayGain of the communication channel on subcarrier i, andis the channel gainIs determined by the estimated value of (c),is the estimation error, is the varianceIndependent zero mean complex gaussian random variables independent of channel gainThe power transmitted by the base station PT to the relay SU;to representA signal on subcarrier i;is represented on subcarrier iComplex white gaussian noise.For relay users SU, i.e. strong users, when employing the cooperative NOMA strategy, andand the coefficients assigned to the assisted weak user wPU are

Stage 1 relay SU application SIC technology to decode self-originated signal and weak user wPU_kAfter the signal, in the second phase, the relay SU forwards the weak user signal, wPU on subcarrier i_kThe received signals of (a) are:wherein the content of the first and second substances,

whereinIndicating PU from a relay user SU to a master user_kGain of the communication channel on subcarrier i, andis the channel gainIs determined by the estimated value of (c),is the estimation error, is the varianceIndependent zero mean complex gaussian random variables independent of channel gainThe power transmitted by the secondary user SU to the weak user PU.

Since the relay SU applies Successive Interference Canceller (SIC) to decode the superimposed signal, the relay SU and the weak user PU signal can be decoded. Since both phases of cooperative NOMA only use half of a time slot, their corresponding rate values are multiplied by 1/2, giving the achievable rate at which the relay SU decodes a weak user PU:wherein the content of the first and second substances,

the estimation error is treated as noise due to imperfect channel estimation.

In phase 1 of cooperative NOMA, the achievable rates achieved by the relay SU are as follows:

in phase 2 of cooperative NOMA transmission, weak user wPU_kThe achievable rate obtained on subcarrier i is:wherein the content of the first and second substances,

the estimation error is treated as noise due to imperfect channel estimation.

And the receiving rate of the corresponding weak user should satisfy the following conditions:

whereinIndicating the total transmission rate from the master base station PT to the relay SU as the sum of equations (3-5) and (3-6). Mainly to limit the transmit power of the relay SU and the transmission rate in the second phase should be less than the transmission rate in the first phase.

Furthermore, using the cooperative NOMA strategy, in order to successfully perform interference mitigation at the relay SU, in practice, the relay SU can successfully decode and cancel the co-channel interference caused by the weak user wPU on the subcarrier by the SIC technique only if the following inequalities hold:

for the main network PN, its total achievable rate on subcarrier i is:

wherein the content of the first and second substances,

as described aboveRespectively representing the capacity of all primary users and the capacity of all secondary users in the primary network, which are all transmitting information via the primary base station. w is a_s,1-w_sThe sub-table represents the weight coefficients assigned to the secondary users SU and the primary user PU. And w_s＜1-w_sThis is because the primary user has a higher priority than the secondary users.Indicating a weak user wPU_kWith secondary usersAnd (4) successfully pairing, and transmitting on the subcarrier i in a cooperative NOMA mode. Otherwise it is 0.Shows that the main base station adopts OMA transmission mode to transmit information to PU_k. Otherwise it is 0. Wherein the equation (3-10) is the total achievable rate of the transmission scheme 1, i.e. cognitive cooperative NOMA-OFDMA transmission scheme 1.

And under the condition that the performance of the primary user PU in the main network is met, the rest subcarriers and the rest secondary users SU are allocated again, if the secondary network only adopts an OMA mode, a cognitive cooperation NOMA-OFDMA shared transmission mechanism is adopted, and if a user with poor receiving reliability in the secondary network is considered and a cooperative NOMA mode is adopted, a cognitive cooperation NOMA-OFDMA free transmission mechanism is adopted.

Whereas for the secondary network, the secondary base station STm e {1, 2., M } uses orthogonal multiple access, which means that each subcarrier can be assigned to signal to the secondary user SU through OMA policy, or to signal to the relay rSU through the policy of C-NOMA.

Specifically, for a given time slot, if SUj e {1, 2.,. J } is assigned subcarrier i and the channel condition from the base station to it is good, then OMA transmission, SU, is used_jThe received signal of (a) may be expressed as:

wherein the content of the first and second substances,

whereinIndicating a secondary base station ST_mTo secondary users SU_jGain of the communication channel on subcarrier i, andis the channel gainIs determined by the estimated value of (c),is the estimation error, is the varianceIndependent zero mean complex gaussian random variables independent of channel gainBase station ST_mTo the power of the SU;indicates the main base station ST_mTransmitting to SU on subcarrier i_jThe signal of (a);indicating SU on subcarrier i_jComplex white gaussian noise.

Then SU correspondingly on subcarrier i_jThe achievable rates are:

wherein the content of the first and second substances,

the estimation error is treated as noise due to imperfect channel estimation.

On the other hand, the secondary base station ST_mWhen transmitting in a coordinated NOMA manner, the relay rSUj_rE {1, 2.., J } and weak users SUj (wSU)_j) Signals are passed from ST by C-NOMA_mAnd (4) superposition and transmission. In the first stage, on subcarrier iThe received signals are:

wherein the content of the first and second substances,

whereinIndicating a secondary base station ST_mTo relay secondary usersGain of the communication channel on subcarrier i, andis the channel gainIs determined by the estimated value of (c),is the estimation error, is the varianceIndependent zero mean complex gaussian random variables independent of channel gainRepresents the power transmitted by the base station PT to the relay SU;to representThe signal on subcarrier i.For relay users SU, i.e. strong users, when employing the cooperative NOMA strategy, andand the coefficients assigned to the assisted weak user wSU are

Stage 1 relay SU application SIC technology to decode self-originated signal and weak user wSU_jAfter the signal, in the second phase, the relay SU forwards the weak user signal, wSU_jThe received signals of (a) are:

wherein the content of the first and second substances,

whereinRepresenting from a relay user SU to a secondary user SU_jOn the sub-carrieri, and the gain of the communication channel, andis the channel gainIs determined by the estimated value of (c),is the estimation error, is the varianceIndependent zero mean complex gaussian random variables independent of channel gainThe power transmitted to the weak user SU for SU.

Since the relay SU applies Successive Interference Canceller (SIC) to decode the superimposed signal, the relay SU and weak user SU signals can be decoded. Since both phases of cooperative NOMA only utilize half of a slot, its corresponding rate value is multiplied by 1/2, giving the achievable rate at which the relay SU decodes the weak user wSU as:

wherein the content of the first and second substances,

the estimation error is treated as noise due to imperfect channel estimation.

In phase 1 of cooperative NOMA, the achievable rates achieved by the relay SU are as follows:

in phase 2 of cooperative NOMA transmission, weak useHouse wSU_jThe achievable rate obtained on subcarrier i is:wherein the content of the first and second substances,

due to imperfect CSI, an estimation error is treated as noise, and thus the snr corresponding to the imperfect CSI is smaller than that of perfect CSI.

And the receiving rate of the corresponding weak user should satisfy the following conditions:

whereinIndicating a secondary base station ST_mThe total transmission rate to the relay SU is the sum of equations (3-17) and (3-18). Mainly to limit the transmit power of the relay SU and the transmission rate in the second phase should be less than the transmission rate in the first phase.

Further, when using the cooperative NOMA strategy, interference mitigation is performed at the relay SU in order to succeed. In practice, the relay SU can successfully decode and cancel the co-channel interference caused by the weak user wSU on the subcarrier by the SIC technique only if the following inequality holds:

for the secondary network SN, its total achievable rate on subcarrier i is:

wherein the content of the first and second substances,

as described aboveIndicating the capacity of all secondary users in the secondary network, which are transmitting information via the secondary base station.Indicating a weak user wSU_jAnd relay usersAnd (4) successfully pairing, and transmitting on the subcarrier i in a cooperative NOMA mode. Otherwise it is 0. And when j equals j_rWhich isSince the same SU is not paired successfully.Indicating that the secondary base station transmits information to SU in OMA mode_jOtherwise, it is 0.

The total system achievable rates are:

the weighted spectral efficiency of the corresponding system can be expressed as:

where B denotes the bandwidth value allocated to the entire system, then B is the sum of the bandwidth values of N subcarriers, and in our system we divide the bandwidth equally into N, then B is N by B_s。

After the channel models and the reachable rates of the main network and the secondary network are analyzed, a formula expression corresponding to the spectrum efficiency of the system can be obtained as shown in the formula (3-25), and then the performance of the system is optimized by taking the spectrum efficiency as a target.

To correspond to the systemThe energy efficiency of (a) is:

wherein, P_n,P_cRespectively, the consumed power of each user and the consumed power of the circuit.

For the trade-off between the spectral efficiency and the energy efficiency, the utility function is constructed, and the corresponding utility function is:

where θ is the spectral efficiency trade-off index and 1- θ is the trade-off index to which energy efficiency is assigned. A trade-off analysis of spectral efficiency versus energy efficiency would be simulated by MATLAB, after which the impact of the trade-off index on system performance is determined by observing the curve changes in the graph.

Finally, constructing a corresponding optimization problem for the multi-carrier multi-user system, and obtaining the maximum system weighted spectrum efficiency by optimizing user selection and power distribution, which can be expressed as:

in the formula: c1 — satisfy the power over NOMA condition, allocate less power for strong users;

c2, ensuring that the transmission rate of the stage 2 adopting the cooperation NOMA strategy in the main network is less than that of the stage 1;

c3-ensuring that the sum of the PT transmission powers from the main base station cannot be greater than the maximum power absorbed by the main base station;

c4 — ensuring that the transmission rate of stage 2 in the secondary network using cooperative NOMA is less than stage 1;

c5-guarantee from Secondary base station ST_mThe sum of the transmitting power cannot be larger than the maximum bearing power of the base station;

c6-ensuring that the sum of the power transmitted from the relay SU cannot be greater than the SU maximum power;

c7-representsThese four values can only take 0 or 1;

c8-guarantee PU has only one transmission mode, i.e. OMA or cooperative NOMA;

c9 — guarantee that each secondary user SU can only have one transmission mode;

c10 — ensuring that SUs in the primary and secondary networks are not reused;

c11 — ensure that each subcarrier can only be allocated to one user or two cooperating users.

The constraints C7-C11 in the above equations (3-28) mainly ensure that only two user information or one user information can be transmitted on each carrier block when OFDMA technology is used in the system, and that only one carrier block can be used for transmitting self information for each user. Therefore, the subcarrier allocation uniqueness and the user pairing uniqueness are ensured. Since the above optimization function is non-convex, it cannot be solved directly with CVX. This optimization problem can be divided into two sub-problems, sub-problem 1: user selection, i.e. subcarrier allocation, is paired with the user, sub-problem 2: and (4) power distribution. For the power distribution problem, a method of continuous iterative convex approximation of convex standard Deviation (DC) can be applied to obtain a suboptimal power distribution coefficient. This is to optimize the cognitive cooperative NOMA-OFDMA free transport mechanismSet to 0, if it is to be set, then to optimize the shared transport mechanismAndset to 0, the transmission scheme 1 is optimized.

(III) solution

Due to the non-convexity of the optimization objective function and the constraint conditions, the optimization objective function is divided into two sub-problems. This section mainly introduces solutions corresponding to two sub-problems, such as sub-problem 1: under the condition of given power distribution, the sub-carrier distribution and the user pairing are carried out by applying a matching theory; and sub-problem 2: under the condition of pairing a given subcarrier with a user, the DC algorithm introduced in chapter III is applied to carry out successive iteration solution.

First, subcarrier allocation and user pairing

In this multi-carrier multi-user cognitive cooperative NOMA network, there are a primary user PU and a secondary user SU, as well as a Primary Network (PN) and a Secondary Network (SN). The primary network is a network for sending information to users through a primary base station, the secondary network is a network for sending information to users through a secondary base station, the primary network comprises a primary user and a relay SU serving a PU, and the secondary network only comprises the SU. Whereas PU's priority is higher than SU. Then the sub-carriers are allocated to the PU and on this basis the relay SU is found to be paired with the weak user PU. And then allocating the sub-carriers which are not allocated to the matched SU through the secondary base station under the condition that all PU performances are met. And supposing that each subcarrier power adopts an average distribution mode, the corresponding user pair adopts a fixed power distribution mode, and then the distribution of the subcarriers and the pair of the users are researched. Given the power allocation, the optimization objective function becomes:

when the transmission power is given, in the main network, the following is derived for equations (3-2), (3-5) — (3-7), respectively:

since their corresponding derivatives are all greater than 0, indicating that the corresponding rate values are an increasing function of the channel gain, the subcarrier allocation and user pairing can be performed through the channel gain.

Based on the theoretical derivation and analysis, a matching algorithm based on the main user channel gain is provided. Firstly, a PU user channel gain matrix H of each subcarrier is established_N×KIn which H is_i,kTo show what is said in the preceding section of this textI.e. the master user PU_kChannel gain at subcarrier i. (1): sorting the user channel gain under each subcarrier from large to small, (2) starting from the maximum channel gain value to distribute the corresponding subcarrier to the corresponding user, if the user is not distributed, then the corresponding user flag bit PU _ flag is distributed_kAnd subcarrier flag bit SC _ flag_iSetting 1 to indicate that the sub-carrier and the user are already allocated, and the corresponding user relation list is assigned with PU _ list_kI-and subcarrier relation list assignment SC _ list_iK is; (3) if the corresponding user is already allocated, comparing which channel gain under the two sub-carriers is larger, and performing re-allocation, so as to continuously and circularly repeat until all sub-carriers or the main user are allocated. The specific algorithm is shown in table 1.

The same idea is similar for re-allocating the remaining sub-carriers in the secondary network, so the explanation is not repeated. And obtaining the allocation condition of the PU and the SU on the subcarrier according to a matching theory.

Table 1 subcarrier allocation algorithm pseudo code based on matching theory

And carrying out user pairing, namely SU and PU or SU and SU according to the allocation conditions of PU or SU on the subcarrier i, namely SC _ list and PU _ list. When there is a PU or SU with poor reception reliability in the primary or secondary network, respectively, i.e. their channel conditions are poor or not within the service range of the base station, the orthogonal multiple access technique OMA cannot be used for transmitting information, so the cooperative NOMA strategy proposed herein is used to assist these weak users in transmitting information, and the relay SU acts as both a relay and a receiver.

For the main network, this subsection proposes a matching algorithm based on cooperative data rates among users. First establish cooperative data rates R with SU under respective weak users wPU_J×KWherein R is_j,kRepresents SU_jAnd PU_kCooperative data rate on subcarrier i. (1): sorting PU cooperation data rate under each SU from large to small, (2) starting from maximum data rate R, allocating the corresponding SU to the corresponding PU, if the user is not allocated, then marking the corresponding PU flag bit PU _ p _ flag_kAnd SU flag SU _ p _ flag_jSet to 1, indicating that the PU and SUj have been allocated and the corresponding PU relationship list is assigned the PU _ pair _ list value_kJ and SU relation list assignment SU _ p _ list_jK is; (3) if the corresponding user is already allocated, the data rate under the two SUs is compared to be higher, so that the allocation is carried out again, and the process is continuously circulated until all the weak users PU or SU are allocated. The specific algorithm is shown in table 2.

Similarly, the idea of pairing users in the secondary network is similar, so the explanation is not repeated. And obtaining the matching condition of the PU and the SU according to a matching theory.

TABLE 2 user pairing algorithm pseudo-code based on matching theory

Second, power distribution

Given a subcarrier assignment and user pairing, the corresponding optimization objective function becomes:

because of the constraint condition and the non-convexity of the objective function, the constraint condition and the non-convexity are correspondingly transformed, and the following results are obtained:

wherein the content of the first and second substances,

and isComprises aThen we can get a sub-optimal solution by successive convex approximation. For any possible pointThe following inequalities exist:

wherein the content of the first and second substances,

same as aboveThe corresponding optimization formula can also be transformed by the above-mentioned transformation, i.e. by converting the convex function part into a linear form using the form of taylor expansion:

the optimization function described above can be solved by CVX. We can get the lower bound by applying an iterative algorithm (algorithm 3) that converges on the locally optimal solution. Then power allocation can be obtainedThe specific algorithm 3 is shown in table 3:

TABLE 3 DC-based Power distribution Algorithm

(IV) simulation results and Performance analysis

Firstly, setting simulation parameters

In order to better show the performance of the transmission model proposed herein, the proposed method was simulated, and the parameter settings are shown in table 4, unless otherwise specified. In the simulation, it is considered herein that K PUs are randomly and uniformly distributed within a circle of a radius of 500m and a correlation distance of 10m from the center of the main base station, but the maximum service distance is 300m due to the main base station. And J SUs are randomly and uniformly distributed in a circular ring with the relevant distance of 10m and the radius of 300m by taking the main base station as the center. Consider that 4 secondary base stations are evenly distributed on a circle with a radius of 300m from the main base station. Considering the demodulation complexity of the SIC receiver, only two users exist in each subcarrier channel, and each user only occupies one subcarrier channel.

TABLE 4 Performance simulation parameters Table

Second, simulation result analysis

In order to reflect the performance of the transmission mechanism provided by the text, the simulation of the spectrum efficiency, fairness and the number of effective access users under perfect CSI and the spectrum efficiency under imperfect CSI are mainly carried out, and compared with the transmission method in the existing literature, and then the related analysis is carried out through a simulation graph. And also for energy efficiency versus spectral efficiency tradeoffs, and then analyzed from simulation graphs.

FIG. 2 shows the results when K is 4, N is 32, w_sError variance from perfect CSI of 1/3Next, by comparing six transmission methods, document [4 ] can be seen]Cooperative cognition of MC-NOMA [5]The cooperative NOMA-CR and OMA direct transport approach is relatively small [5 ]]The reason for the slow rise of the curve(s) is that the Primary Network (PN) uses four levels of PU cooperative NOMA, the secondary network performsThe frequency spectrum is shared, and the mutual interference is more; document [4 ]]The curve of (a) is relatively gentle because it uses one secondary base Station (ST) as a relay to transmit the PU and SU information by superposition in the NOMA mode, without considering the PU at each edge. Using two power distribution modes, i.e. fixed power distribution (FPA, a)₁0.2) and DC, the performance after optimization is better than that of FPA. The cognitive cooperative NOMA-OFDMA transmission mechanism only considers the PU of the main network, and when there is a user with poor reception reliability, the two-stage cooperative NOMA strategy proposed herein in which the SU serves as a relay is adopted, and the sub-carriers are only allocated to the main network, so that the remaining sub-carriers are not allocated, the spectrum resources are wasted, and the unallocated SU is not served, and thus the spectrum utilization rate is low. Cognitive cooperative NOMA-OFDMA shares the transmission scheme, which, like the above-mentioned scheme, matches subcarriers with users in the primary network, but also considers the secondary network, and reallocates the remaining subcarriers with SUs, so that the spectrum resources can be fully utilized. The corresponding free transmission mechanism also considers the secondary network, but it considers the edge users of the SN, so that although the capacity, i.e. the spectrum efficiency, of the relay SU is lower than that of the free mechanism, the corresponding fairness, the energy efficiency and the effective user access amount are better than those of the sharing mechanism, and then a simulation figure shows this fact. It can be seen from simulation that the cooperative NOMA approach proposed here to act as a relay and receiver between a weak user and a base station with SUs with good channel conditions is superior to the one with ST as a relay or with OMA direct transmission, and SUs are randomly distributed and in large numbers, thus serving more weak users.

Fig. 3 shows the CSI at perfect CSI, K4, N32, w_s1/3 and a power distribution coefficient of a₁The fairness performance of the free transmission scheme is highest and the shared transmission scheme is the second best at 0.2. Corresponding fairness performance evaluation Jain's fairness index formulation, i.e.Where N is the number of users of the system. Whereas the cognitive cooperative NOMA-OFDMA transmission mechanism, which only considers the primary network, does not consider secondary network users, so with SUIts fairness is decreased. Document can be found when SU increases [4]Is higher than [5 ]]Then less than [5 ]]This is because of document [5 ]]Sharing of spectrum in secondary networks, taking into account SU users of the secondary networks [4 ]]The PU and SU are served in power domain NOMA mode only with the secondary base station acting as a relay, so the SU is served only when the PU reception reliability is poor. While OMA direct transmission is adopted in the primary network for OMA and does not take into account cognitive networks, its performance will be lower as SU increases, which starts higher because it may lose the capacity of the relaying PU as it adopts cooperative NOMA in the primary network. The reason why the proposed free transmission method is superior to others is that a plurality of SUs are distributed randomly, more weak users can be served.

Fig. 4 shows the CSI at perfect CSI, N-32, w_sPower distribution coefficient a of 1/3 to relay SU₁At 0.2, the average data rate is 0.5bps/Hz [7 ] at the minimum user]To determine whether it is a valid access user. If the number is larger than the preset number, the access user is valid, otherwise, the access user is not valid. The free transmission mechanism corresponds to the highest number of access users, and the shared transmission mechanism is secondary. The corresponding cognitive cooperative NOMA-OFDMA transmission scheme, which only considers the primary network, is therefore not considered by the corresponding secondary network users, whose number of access users is small compared to the other two. When SU increases continuously, document [5 ] can be found]First higher than the document [4 ]]And then less than in literature [4 ]]This is because of document [5 ]]Using 4 inter-PU cooperative NOMA in the primary network, but not in the secondary network, the corresponding edge users cannot be fully considered, document [4 ]]With secondary base stations acting as relays serving PU and SU in power domain NOMA, the considered edge users are better than in document [5 ]]Much more. For OMA direct transmission, the orthogonal multiple access technology is adopted in the main network, and the number of corresponding access users is relatively low without considering the secondary network. The number of access users of the free mechanism proposed herein is higher than that of the shared mechanism, because the number of effective access users increases when users with poor channels are considered in both networks.

Fig. 5 shows the results when K is 4, J is 16, N is 32, w_s1/3 sum and relay SU user power distribution coefficient is a₁At 0.2, with channel estimation errorVariance value ofIncreasing, the corresponding spectral efficiency decreases, mainly due to the fact that under imperfect CSI, there is an estimation error, the corresponding estimation error is treated as a kind of noise, which results in a decrease of the signal-to-noise ratio (SNR), and the corresponding transmission rate decreases with the decrease of the SNR. In the corresponding three transmission modes, the spectrum efficiency of the corresponding shared transmission mode is higher than that of the free mode, and the transmission mode considering the main network is the lowest.

Fig. 6 shows the CSI at perfect CSI, N-32, w_s1/3 power distribution coefficient of relay SU in cooperative NOMA is a₁At 0.2, a simulation diagram is mainly aimed at the cognitive cooperative NOMA-OFDMA free transport mechanism proposed herein. The spectrum efficiency of the free transmission mechanism increases with the increase of the number of the primary users PU and the secondary users SU, because the spectrum efficiency of the system increases as the number of users increases and the number of users accessed by the system increases under the condition that the subcarriers are not allocated. Therefore, the corresponding free mechanism can improve the utilization efficiency of spectrum resources and increase the user access amount, because the transmission mechanism adopts cooperative NOMA in the main network and the secondary network, namely one subcarrier can serve two users, the transmission of edge users is assisted, and the fairness of the system is improved.

Fig. 7 shows the CSI at perfect CSI, K4, N32, w_sPower distribution coefficient of 1/3 and relay SU is a₁Under 0.2, the average user data rate of the cognitive cooperative NOMA-OFDMA free transmission mechanism SU increases as the number of SUs increases, because the system subcarriers are not allocated, and as the number of SUs increases, the more SU the system accesses, the more SU the average user data rate of the SU increases. And when the sub-carriers are allocated, the corresponding curve tends to be flat gradually. Whereas for a PU, since its number is 4, it increases relatively slowly as SU increases, and its data rate remains almost constant when the number of PUs is smaller than the number of secondary users SU. And the performance of the corresponding PU is higher than the performance of the PU using OMA direct transport.Mainly, because the cooperative NOMA policy is adopted by the free transmission mechanism, the corresponding edge user is served, so the performance of the edge user is improved, and when the number of the PUs is less than the number of the SUs, the number of the SUs correspondingly accessed by the main network is not changed so much, and the performance of the corresponding performance primary user is not changed too much. Therefore, the proposed cooperative NOMA policy may improve the performance of the main network and may increase the amount of user access.

Fig. 8 shows the power distribution coefficient a for the sum and relay SU at perfect CSI, J32, N32₁At 0.2, consider different systems where the cognitive cooperative NOMA-OFDMA transmission scheme of the primary network is combined with the free transmission scheme where the number of primary users PU is 4 or 16. Mainly analyzes the influence of SU weight value on the system performance. It can be observed that the spectral efficiency of cognitive cooperative NOMA-OFDMA systems is a function of the SU weight w_sIncreases and decreases, while the spectral efficiency of cognitive cooperative NOMA-OFDMA free transmission systems is a function of SU weight w_sAnd increases with an increase. This is because PU and SU occupy different proportions in different networks. There is a trade-off between the performance of the primary and secondary networks. Can be set by setting w_sThe value of (2) is flexibly adjusted to adapt to various scenes. In addition, for the same w_sThe spectral efficiency of both networks increases with the increase of PUs. As can be seen from simulation analysis, multi-user diversity generally brings extra throughput gain to the system, and therefore, the spectrum utilization rate of the system can be improved.

Fig. 9 shows the system utility values obtained after the trade-off of spectral efficiency and energy efficiency corresponding to three transmission schemes. Where θ is 2/3, K is 4, N is 32, w_s1/3, and the error variance at perfect CSI isThe power distribution coefficient of the AND-and-Relay SU is a₁At 0.2, the utility value of the corresponding free transmission scheme is the highest, and then the transmission scheme is shared the second time, and the lowest is to consider only the users in the main network and not to allocate the remaining subcarriers to the remaining SUs. This is mainly due to the high weight of spectral efficiency, while the free transmission mechanismThe corresponding spectrum, although lower than the shared scheme, is more energy efficient than the shared transmission scheme, so in this case it corresponds to a higher U-value than the shared transmission scheme. The coefficient value θ will be specifically analyzed thereafter.

Fig. 10 shows that at perfect CSI, K4, J16, N32, the utility function of the system varies with the coefficient value, which is a way to trade off spectral efficiency from energy efficiency, when the coefficient is 0, it corresponds to energy efficiency, it can be seen that the cognitive cooperative NOMA-OFDMA transmission scheme is the most energy efficient because its corresponding remaining subcarriers are not reused, consume less power, when it is greater than 0.38, the system utility value of the free scheme is higher than the above-mentioned transmission scheme, and as the coefficient value gradually increases as shown by 0.74, its corresponding system utility value is lower than both the free and shared transmission schemes; and when it is about 0.756, the utility value of the sharing mechanism is higher than that of the free mechanism, because the coefficient is increased and the weight of the spectrum efficiency is larger.

(V) conclusion

The present subject matter is directed to Enhanced Mobile Broadband (eMBB), massive Machine Type Communication (mtc), ultra Reliable Low Latency Communication (urrllc), and the need for high data rate in human life, which are three application scenarios of 5G, and related research is performed. Research shows that cognitive radio, NOMA, cooperative communication technology and OFDMA have the advantage of improving the spectrum efficiency of the system, and the three technologies are organically combined to improve the performance of the system. Therefore, three transmission mechanisms are proposed, and a layer-by-layer progressive relation is formed between the three transmission mechanisms, namely a free mechanism is optimal, and a sharing mechanism is arranged in the second place. The free mechanism improves the frequency spectrum efficiency and the energy efficiency of the system and improves the number of effective access users. The main research results herein are as follows:

(1) a new cooperative NOMA strategy is proposed in which the secondary user SU acts as a receiver and relay between the transmitter and the weak user to improve the weak user throughput. Since the plurality of SUs are randomly distributed, the performance of more weak users can be guaranteed. Therefore, the proposed cooperative NOMA strategy provides better spectrum efficiency and user fairness than the existing cooperative strategy, and a fixed secondary base station serving as a relay cannot give consideration to users with poor receiving reliability at various places, which is not enough to ensure system performance, especially under the condition of more weak users.

(2) Three transmission scheme strategies are proposed, namely transmission scheme 1: cognitive cooperative NOMA-OFDMA transport mechanism (consider only the primary network and employ OMA and cooperative NOMA strategies in the primary network), transport mechanism 2: cognitive cooperative NOMA-OFDMA shared transport mechanism (OMA policy only in secondary networks based on OMA and NOMA policy adopted in primary networks), transport mechanism 3: cognitive cooperative NOMA-OFDMA free transport mechanism (OMA and cooperative NOMA strategies are employed in both the primary and secondary networks). And for the last mechanism, namely the free transmission mechanism, the proposed cooperative NOMA strategy is applied to the main network and the secondary network to ensure more users with poor receiving reliability of the system. It is worth noting that since the SU can flexibly change its transmission mode in both networks through a matching algorithm. If a cooperative NOMA strategy can be adopted in the main network to assist the weak user PU, the information of the user is received and decoded in the time slot 1, and the information of the weak user PU is helped to be forwarded in the time slot 2; or the weak user SU can be assisted in the secondary network by means of cooperative NOMA; OMA direct transport may also be employed in the secondary network. The mode improves the spectrum efficiency, the fairness and the effective access user number of the system. Whereas the secondary user SU of the free transmission technique proposed herein has a higher degree of flexibility with respect to the prior document, for SU only one way, i.e. only one receiving user.

(3) Under OFDMA technology, resource allocation is performed in conjunction with the primary network and the secondary network. And optimizing by taking the optimized spectrum efficiency as a target. The matching algorithm and the DC algorithm are adopted to solve the problems of user selection and power distribution respectively. In addition, the correlation performance analysis of the cooperative NOMA strategy and three transmission mechanisms under perfect and imperfect conditions is also analyzed, a utility function is also constructed to balance the spectrum efficiency and the energy efficiency of the system, and the method can be seen thatSelecting different transmission modes in different scenes, and if the number of SUs is smaller than that of the PU and the corresponding energy efficiency requirement is high, adopting a transmission mechanism 1; and when the number of SU is large and the requirement on the number of users accessing the system, fairness and spectrum efficiency is high, a free transmission mechanism can be adopted. But also analyzes the SU weighting factor w_sImpact on system performance.

Example two:

the present embodiment provides a control device of a communication system, including: a processor and a memory, the memory storing a computer program that can be called by the processor, the computer program, when called, performing the method according to the first embodiment.

The present embodiment also provides a communication system, including: such as the control device described above.

The embodiment also provides a computer storage medium, which stores a computer program, and the computer program is called by a processor to execute the method according to the first embodiment.