阅读说明：本技术 用于使用低位模数转换器进行数据检测的设备和方法 (Apparatus and method for data detection using low-order analog-to-digital converter ) 是由 N·李 Y-S·全 O·奥尔汗 S·塔瓦尔 于 2018-01-16 设计创作，主要内容包括：公开了一种用于检测通过无线信道发送的数据的设备和方法。例如,对于多个接收天线中的每个接收天线,该方法通过ADC将由接收天线接收的模拟信号转换成相应的数字信号,并且对于多个接收天线中的每个接收天线,该方法通过信道变换器对数字信号进行信道变换,以确定数字信号的相应的等效整数表示,并且方法由接收组合器通过接收组合为多个接收天线确定的数字信号的相应的等效整数表示来检测数据。(An apparatus and method for detecting data transmitted through a wireless channel are disclosed. For example, for each of the plurality of receive antennas, the method converts an analog signal received by the receive antenna into a corresponding digital signal by the ADC, and for each of the plurality of receive antennas, the method channel-transforms the digital signal by the channel transformer to determine a corresponding equivalent integer representation of the digital signal, and the method detects data by the receive combiner by receiving the corresponding equivalent integer representations of the digital signal determined for the plurality of receive antennas.)

1. An apparatus for detecting data transmitted over a wireless channel, the apparatus comprising:

analog-to-digital conversion (ADC) means for converting, for each of a plurality of receiving antennas of a receiver device, an analog signal received by said receiving antenna into a corresponding digital signal;

channel transformation means for channel transforming the digital signal to determine a respective equivalent integer representation of the digital signal for each of the plurality of receive antennas; and

receive combining means for detecting data by receiving the respective equivalent integer representations of the digital signals determined by combining the plurality of receive antennas.

2. The apparatus of claim 1, wherein the channel transform is based on a known effective channel matrix.

3. The apparatus of claim 1, wherein the ADC comprises a 1-bit ADC.

4. The apparatus of claim 1, wherein the ADC comprises a P-stage scalar quantizer.

5. The apparatus of claim 1, wherein the P-level scalar quantizer comprises a sawtooth transform.

6. The apparatus of claim 5, wherein when the P-level scalar quantizer is a sawtooth transform, the sawtooth transform is implemented by a scalar quantizer followed by a modulo operator.

7. The apparatus of claim 1, wherein the detected data is provided to a demodulation means of the receiver apparatus.

8. The apparatus of claim 1, wherein the receive combining comprises selecting a receive antenna from among the plurality of receive antennas.

9. The apparatus of claim 8, wherein the selected receive antennas provide the subchannels with the highest channel capacity.

10. The apparatus of claim 8, wherein the selected receive antenna is identified by determining the subchannel with the smallest entropy of effective noise.

11. The apparatus of claim 1, wherein the receiving combining comprises applying a majority decoding principle when using repetition coding on a spatial domain.

12. The apparatus of claim 11, wherein the repetition coding in the spatial domain is used to send the same data to the multiple receive antennas over different respective multiple subchannels.

13. The apparatus of claim 1, wherein the receiving a combination comprises detecting the data by identifying a linear block code having a minimum distance from the equivalent integer representation of the digital signal.

14. The apparatus of claim 11, wherein the identification of the linear block code having the minimum distance is based on a known effective binary channel matrix and a known set of all possible linear block codes sent to the plurality of receive antennas.

15. The apparatus of claim 1, wherein the receiving combining comprises detecting the data by performing inter-stream interference cancellation.

16. The apparatus of claim 15, wherein the inter-stream interference cancellation is performed using an inverse of an effective binary channel matrix known by the receiver apparatus.

17. The apparatus of claim 16, wherein the detecting of the data by using the inverse of the effective binary channel matrix is performed when a number of transmit antennas of a transmitter apparatus is equal to a number of receive antennas of the receiver apparatus.

18. The device of claim 16, wherein the detection of the data by using the inverse of the effective binary channel matrix is performed by selecting a number of receive antennas equal to the number of transmit antennas of the transmitter device when the number of receive antennas of the receiver device is greater than the number of transmit antennas of the transmitter device.

19. The apparatus of claim 1, wherein the inter-stream interference cancellation is performed when the data is encoded using a series of nested linear codes.

20. A wireless device, comprising:

a receive antenna array configured to receive a plurality of signals; and

the apparatus for detecting data transmitted over a wireless channel of claim 1.

21. The wireless device of claim 20, wherein the wireless device is a user equipment device or a base station.

22. A method for detecting data transmitted over a wireless channel, the method comprising:

for each of a plurality of receive antennas, converting, by an ADC, an analog signal received by the receive antenna into a corresponding digital signal;

for each of a plurality of receive antennas, channel transforming the digital signal by a channel transformer to determine a respective equivalent integer representation of the digital signal; and

detecting, by a receive combiner, data by receiving the respective equivalent integer representations of the digital signals determined by combining the plurality of receive antennas.

23. The method of claim 22, wherein the detecting data by receiving a combination comprises one of:

selecting a receiving antenna from among the plurality of receiving antennas;

when using repetition coding in the spatial domain, most of the decoding principles are applied;

detecting the data by identifying a linear block code having a minimum distance to the equivalent integer representation of the digital signal; and

the data is detected by performing inter-stream interference cancellation.

24. An apparatus, comprising:

a processor; and

a memory configured to store program instructions to be executed by the processor, wherein execution of the program instructions causes the processor to perform operations for detecting data transmitted over a wireless channel, the operations comprising:

for each of a plurality of receive antennas, converting, by an ADC, an analog signal received by the receive antenna into a corresponding digital signal;

for each of a plurality of receive antennas, channel transforming the digital signal by a channel transformer to determine a respective equivalent integer representation of the digital signal; and

detecting, by a receive combiner, data by receiving the respective equivalent integer representations of the digital signals determined by combining the plurality of receive antennas.

25. The apparatus of claim 24, wherein the detecting data by receiving a combination comprises one of:

selecting a receiving antenna from among the plurality of receiving antennas;

when using repetition coding in the spatial domain, most of the decoding principles are applied;

detecting the data by identifying a linear block code having a minimum distance to the equivalent integer representation of the digital signal; and

the data is detected by performing inter-stream interference cancellation.

Technical Field

The present disclosure describes methods and apparatus for performing data detection using a low-order analog-to-digital converter (ADC). Although the method is described for detecting data transmitted over a wireless channel of a Long Term Evolution (LTE) network, the detected data may be data transmitted using any type of wireless network (e.g., a 3G network, a 5G network, etc.).

Background

Wireless communication services may be provided via different types of networks (e.g., LTE networks, etc.). Any number of User Equipments (UEs) may communicate via each base station (e.g., eNodeB). As the number of UEs continues to grow, there is an increasing demand for supporting data rates of hundreds of Gbps. In order to support high data rates, a communication system having a large capacity is required. The capacity of a communication system increases linearly with bandwidth.

One method of supporting very high data rates may be to use an ultra-wideband communication system. For example, wireless networks beyond LTE (e.g., 5G networks) may need to rely on ultra-wideband systems to deliver data rates of hundreds of Gbps. However, as the bandwidth of communication systems increases, high speed ADCs are required. Unfortunately, the energy efficiency of the ADC drops dramatically when the sampling rate exceeds 100 MHz.

One way to improve energy efficiency is by using low resolution ADCs. Low resolution ADCs also reduce circuit complexity. As such, communication systems using very low resolution ADCs have received increasing attention for applications requiring high speed sampling. However, once a very low resolution ADC is employed, the capacity of the communication system is fundamentally limited by the quantization level. In other words, it is challenging to provide the desired data rate while meeting resolution and power requirements. For example, as an example, assume that a 1-bit ADC is used. Quadrature Phase Shift Keying (QPSK) modulation is then information-optimized for single-input single-output (SISO) fading channels. Thus, 2 bits/sec/hz is the maximum spectral efficiency of a SISO communication system using a 1-bit ADC.

One method for compensating for the limitation of spectral efficiency is by using multiple antennas. The spectral efficiency of a communication system increases linearly with the number of receive antennas. Therefore, ultra-wideband massive multiple-input multiple-output (MIMO) communication systems operating with low resolution ADCs have the potential to be the communication system of choice for future networks. Large-scale MIMO systems can be designed to provide the required high capacity while being energy efficient. High capacity may be suitable for supporting future cellular and WiFi communication networks. However, conventional MIMO schemes for detecting data are developed for channels that can be represented as linear channels. Thus, conventional MIMO schemes for detecting data are suboptimal when using low resolution ADCs.

Drawings

The teachings of the present disclosure can be more fully understood by reading the following detailed description and examples in conjunction with the accompanying drawings, in which:

FIG. 1 illustrates a wireless network for providing services to wireless devices;

fig. 2 illustrates an apparatus for performing data detection on a received signal in accordance with the teachings of the present disclosure;

FIG. 3 shows a flow diagram of an example method for detecting data according to the present disclosure; and

fig. 4 illustrates an apparatus for performing the functions described in this disclosure.

To facilitate reading, identical reference numerals have been used, where possible, to designate identical elements that are common to the figures.

Detailed Description

The present disclosure relates to an apparatus and method for detecting data. For example, the teachings of the present disclosure may be used to detect data using a low-bit ADC, where the data is transmitted for communication over a wireless network (e.g., a Long Term Evolution (LTE) network, a 5G network, etc.).

As described above, the conventional MIMO scheme for detecting data is developed for a linear channel. This means that the scheme is based on the assumption that the output value of the ADC is proportional to the input value. It is further noted that the ADC quantizes the received signal using a stepped quantizer. The stepped quantizer may be a uniform or non-uniform quantizer. The high resolution quantizer may maintain a linear relationship between the input and output values of the ADC. The use of a low resolution ADC changes the MIMO channel from a channel that can be represented as linear to a channel that can no longer be represented as linear. In other words, when a low resolution stepped quantizer is used, the resulting MIMO channel is no longer a linear channel. Therefore, conventional MIMO schemes for detecting data developed for linear channels are highly undesirable.

The present disclosure relates to an apparatus and method for detecting data by interpreting a MIMO channel with a low resolution ADC as a linear MIMO channel over a limited domain. When the ADC uses n bits and n is a small integer, the resolution is referred to as "low level resolution". For example, n is 1, …, 5.

Fig. 1 illustrates a wireless network 100 for providing services to wireless devices. The wireless network includes a transmitter wireless device 110 and 112 and a receiver wireless device 114 and 116 that communicate over a wireless channel 120. For example, the transmitter wireless device may be a user equipment and the receiver wireless device may be a base station. In another example, the transmitter wireless device may be a base station and the receiver wireless device may be a user equipment.

Each of the transmitter wireless devices may include any number of transmit antennas. Similarly, each of the receiver wireless devices may include any number of receive antennas.

For the illustrative example, assume that wireless channel 120 is a channel of a MIMO communication system and that channel 120 is used to support N_tA transmitting antenna and N_rCommunication between receiving antennas, the communication system may be referred to as N_t×N_rA MIMO system. For example, a 4 x 4MIMO system may support 4 transmit antennas and 4 receive antennas. When N is present_tIs equal to 1 and N_rMore than 1, the communication system may be referred to as a single-inputIn-multiple-output (SIMO) systems. Similarly, when N is_rIs equal to 1 and N_tMore than 1, the communication system may be referred to as a Multiple Input Single Output (MISO) system. Note that each antenna may be associated with a unique wireless device, or multiple antennas may be associated with the same wireless device. For example, 4 transmit antennas in a 4 x 4MIMO system may be on the same transmitter wireless device. For purposes of this disclosure, each receiver wireless device may then include up to N_rA receiving antenna.

Those of ordinary skill in the art recognize that the antennas of the present disclosure may be antennas of transceivers that may be used to transmit and receive wireless signals. For clarity, the present disclosure is described using "receive antennas" and "transmit antennas" with respect to the direction of transmission. The receiver and transmitter portions of the transceiver antenna may be described separately without loss of generality or with the addition of limitations on the implementation.

Fig. 2 illustrates an apparatus 200 for performing data detection on a received signal in accordance with the teachings of the present disclosure. The device 200 is included within each of the receiver wireless devices 114 and 116 described above with respect to fig. 1. The apparatus 200 includes an ADC210, a channel changer 220, and a detector 230. It should be noted that the detector 230 performs data detection by combining signals received via multiple receive antennas. As such, the detector 230 may also be referred to as a receive combiner.

For each of a plurality of receive antennas of the receiver device, the ADC210 is configured to convert an analog signal received by the receive antenna into a corresponding digital signal. For example, assume that the digital equivalent of the signal received by a particular receive antenna is stored in a matrix. An estimated channel matrix may then be defined, where each element of the estimated channel matrix comprises a digital equivalent of an analog signal received by a particular receive antenna.

In one aspect, the ADC comprises a 1-bit ADC. In one aspect, the ADC includes a P-level scalar quantizer. In one aspect, the step size of the P-level quantizer is selected based on a transmit power constraint signal-to-noise ratio (SNR). In one aspect, the P-level scalar quantizer comprises a sawtooth transform. In one aspect, when the P-level scalar quantizer is a sawtooth transform, the sawtooth transform may be implemented by a scalar quantizer followed by a modulo operator. In one aspect, the signals received by the receive antennas comprise signals transmitted by any number of transmit antennas.

For each of the plurality of receive antennas, the channel transformer 220 is configured to channel transform the digital signal to determine a corresponding equivalent integer representation of the digital signal. For example, for a 1-bit ADC, the channel transformation may transform the output of the AC210 into an equivalent binary representation. The channel transformation is based on a known effective channel matrix.

The receive combiner 230 is configured to detect the data by receiving respective equivalent integer representations of the digital signals determined by combining the multiple receive antennas. Once the receive combining is complete, the detected data may be provided to a demodulator of the receiver device.

In one aspect, receive combining includes selecting a receive antenna from a plurality of receive antennas. In one aspect, the selected receive antenna provides the subchannel with the highest channel capacity. For example, assume that there are three receive antennas. Then, there are three subchannels, where each subchannel is associated with a particular receive antenna. Then, the reception combination may select a reception antenna having the highest capacity from among the three reception antennas.

In one aspect, the selected receive antennas are identified by determining the subchannel with the least entropy of the effective noise. Determining the subchannel with the minimum entropy of the effective noise is also described below in example a.

In one aspect, receiving the combination includes applying a majority decoding principle when using repetition coding on the spatial domain. In one aspect, repetition coding in the spatial domain is used to transmit the same data to multiple receive antennas over different respective multiple subchannels.

In one aspect, receiving the combination includes detecting the data by identifying a linear block code having an equivalent integer representing a minimum distance from the digital signal. In one aspect, the identification of the linear block code having the smallest distance is based on a known effective binary channel matrix and a known set of all possible linear block codes transmitted to the plurality of receive antennas. A method for implementing the determination of a linear block code with minimum distance is also described below in example a.

In one aspect, receiving the combination includes detecting the data by performing inter-stream interference cancellation. In one aspect, inter-stream interference cancellation is performed using the inverse of an effective binary channel matrix. The effective binary channel matrix is known to the receiver. In one aspect, inter-stream interference cancellation is performed when data is encoded using a series of nested linear codes.

In one aspect, detecting data by using an inverse of an effective binary channel matrix is performed when a number of transmit antennas of a transmitter device is equal to a number of receive antennas of a receiver device. In one aspect, when the number of receive antennas of the receiver device is greater than the number of transmit antennas of the transmitter device, detecting data by using an inverse of an effective binary channel matrix is performed by first selecting a given number of receive antennas, where the given number is equal to the number of transmit antennas of the transmitter device, and then using the inverse of the effective binary channel matrix for the selected receive antennas. That is, when the channel is symmetric, inversion is performed. The inverse of the effective binary channel matrix may be calculated as long as the determinant of the effective binary channel matrix is not zero. This means that the channels of the selected receive antennas are linearly independent. Detecting data by performing inter-stream interference cancellation is also described in example a.

In one aspect, receiving the combination includes detecting the data by performing a plurality of the following: selecting a receiving antenna from among a plurality of receiving antennas; when using repetition coding in the spatial domain, most of the decoding principles are applied; detecting data by identifying a linear block code having an equivalent integer representing a minimum distance from a digital signal; and detecting data by performing inter-stream interference cancellation. For example, receive combining may be performed by first selecting a subset of receive antennas from among a plurality of receive antennas, followed by performing inter-stream interference cancellation detection data. For example, if there are more receive antennas than transmit antennas, the selection of the subset may be to have the same number of transmit and receive antennas. Detection may then be performed by using the inverse of the effective binary channel matrix. It should be noted that the effective binary channel matrix for the subset of receive antennas is small and, therefore, computation is simplified.

Fig. 3 illustrates a flow diagram of an example method 300 for detecting data in accordance with this disclosure. An example of an implementation of method 300 is provided in "example a" below.

In one aspect of the disclosure, method 300 may be implemented in a wireless device that includes an array of receive antennas configured to receive a plurality of signals, and a device (e.g., device 200) for detecting data from the plurality of received data. For example, the method 300 may be implemented in the device 200, where the conversion is performed by the ADC210, the channel conversion is performed by the channel transformer 220, and the receive combining is performed by the receive combiner 230 to detect the data. In another example, the method 300 may be implemented in the apparatus 400 described below.

The method 300 begins at step 305 and proceeds to step 310.

In step 310, for each of a plurality of receive antennas, the method converts, by the ADC210, the analog signal received by the receive antenna into a corresponding digital signal.

In step 320, for each of the plurality of receive antennas, the method channel transforms the digital signal by channel transformer 220 to determine a corresponding equivalent integer representation of the digital signal.

In step 330, the method detects data by the receive combiner 230 by receiving a corresponding equivalent integer representation of the digital signal determined by combining the multiple receive antennas. Step 310-. The method may then proceed to step 340 to end the detection of the data or to step 305 to receive more signals from which more data is detected in accordance with the present disclosure.

Fig. 4 illustrates an apparatus 400 for performing the functions described in this disclosure. The device 400 includes a processor 401 and a memory 402 configured to store program instructions to be executed by the processor 401, wherein execution of the program instructions causes the processor 401 to perform operations for detecting data from a plurality of signals received over a wireless channel, the operations including converting, channel transforming, and receiving the combination. Device 400 may also include any number and type of input/output devices 403.

It should be noted that although fig. 4 illustrates a single device, the method 200 may be implemented via any number of devices performing the operations of the method 300 in a distributed manner, a serial manner, or a combination thereof. Further, the appliance may be a virtualized appliance instantiated on a server (e.g., a server of a cloud network). As such, the representation of the hardware components of the device may be a virtualized or physical representation without departing from the teachings of the present disclosure. Thus, the method 300 may be implemented in hardware, software, or a combination thereof. It should be noted that the processor 401 executing the program instructions includes the processor 401 executing, directly or indirectly, the operations of the method 300. For example, the processor 401 may perform operations in conjunction with other devices or may direct another device to perform operations.

It should be understood that aspects of the present disclosure are described above by way of example. The various aspects are illustrative, however, and not restrictive. Accordingly, the scope of the disclosure should not be construed as limited by any of the above aspects or examples. The breadth and scope of the present disclosure should be defined in accordance with the scope and breadth of the following claims and/or equivalents.

Example a: communication system implementing data detection method of the present disclosure

It is assumed that the communication system of fig. 1 between the transmitter device and the receiver device is considered. Further, assume that the transmitter device is equipped with N_tA transmitting antenna, a receiver device is provided with N_rA receiving antenna, and N_r≥N_t。

At a given time slot N, it is assumed that the transmitter device will be N_tMultiple multi-codeword vectorsTo the receiver device.

Each receive antenna receives some combination of the signals transmitted by the transmit antennas. Suppose thatRefers to the channel matrix. It should be noted that H is known to the receiver. Further, assume that the received signal includes additive gaussian noise with zero mean and unit variance. Can be composed ofAdditive gaussian noise is referred to. The received signal vector before quantization (i.e., before applying the ADC) may then be defined as N_rA plurality of vectorsWherein y [ n ]]＝H x[n]+ z. Receiving a signal (i.e., vector y n]) Is the input to the ADC.

Step 310

Assume that the ADC is a 1-bit ADC (i.e., an ADC having two levels). The function of the operation performed by the ADC is then to convert each received signal into one of the quantization levels. In other words, if Q₂Represents the function of ADC, thenFor receive antenna m, at time slot n, the output of the ADC may be expressed as:

wherein h is_m，lIs the (m, l) th element of H, x_l[n]Is x [ n ]]The ith element of (1), and z_m[n]Is the noise of the receiving antenna m. Note that after step 310 is performed, y_m[n]E {0, 1 }. In other words, based on the result quantized by the ADC, y [ n ]]Has a value of "0" or "1".

Step 320

In step 320, for each receive antenna m, the signal converter converts the output of the ADC into an equivalent binary representation. In one aspect, the transformation is based on an effective channel matrix. Between a transmitter and a receiverEffective channel matrix ofAnd (4) showing. Then, for antenna m, at time slot n, the output of channel transformer 220 may be represented by:

wherein

Refers to addition over a finite field, and

a_m，lis the (m, l) th element of A, andis the effective noise.

Step 330

In step 330, the receiver combiner represents the detected data by receiving respective equivalent integers of the digital signals determined by combining the plurality of receive antennas. Receive combining may be implemented using one or more of a-D, as described below.

A.Receive combining by determining a subchannel with minimum entropy of effective noise

As described above, determining the subchannel having the highest capacity is the same as determining the subchannel having the smallest entropy of the effective noise. It is assumed that a parallel binary symmetric channel model is applied to the binary representation in the above formula. The subchannel with the highest capacity may then be selected as follows. First, an antenna index i^*Can be defined to refer to the receive antenna with the least entropy of the effective noise. Then, i can be determined as follows^*Appropriate values of (c):

wherein p is_iIs used for the pairParameters of the bernoulli random variables being modeled.

The function for performing receive combining can then be defined as a linear matrix, except when both the columns and rows are i^*Except time, all elements are zero. When both column and row are i^*The elements of the matrix are equal to 1. In other words, f (y [ n ]])＝Wy[n]Where for i, j e {1, 2_r}/{i^*W (i, j) ═ 0, and W (i)^*，i^*) 1. Then, f (y [ n ]]) Is an estimate of the detected data. The receiving antenna with the highest capacity is selected and then the estimate of the detected data is based on the receiving antenna with the highest capacity.

B.Receive combining by applying majority decoding principles

As described above, when the same data is transmitted to the receiver device via a plurality of subchannels by the transmitter device, the reception combining by applying the majority decoding principle is performed.

For example, assume that the transmitter device includes one transmit antenna and the receiver device includes a receive antenna. Also assume that the transmission data is "1" for slot 1. In other words, x₁[1]1 is sent via one transmit antenna. From y 1]＝[y₁[1]，y₂[1]，y₃[1]]^TGiving a received output vector, where for m e 1, 2, 3,assume that the equivalent integer representations of the digital signal are y for receive antennas 1, 2, and 3, respectively, as determined in step 320₁[1]＝1、y₂[1]＝1、y₃[1]0. Then, y [1 ]]＝[1，1，0]^T. Since the same information (e.g., x) is transmitted through three different sub-channels₁[1]1), then the scenario means that the first two sub-channels have good quality and the last sub-channel has good qualityNoise in the traces inverts the output. An estimate of the detected data can then be determined by applying a majority decoding principleFor the above example, the combined output 1 is received asIs estimated. In other words,

when the number of receiving antennas is N_rBy applying majority decoding principles for receive combining to find at slot nThe estimate of (d) can be written as:

whereinIs a summation operation.

C.Reception group by identifying a linear block code having a minimum distance expressed by an equivalent integer from a digital signal Combination of Chinese herbs

As described above, the receiver knows the valid binary channel matrix. Furthermore, the receiver knows all possible codewords that can be transmitted by the transmitter device. For example, for N_tA transmitting antenna existsA possible input vector. Each of the possible input vectors is a candidate for being a transmission code.

Then, the receiver isEach of the possible input vectors creates a codeword vector. In other words, the receiver createsA vector of code words ofEach codeword vector is created for a respective one of the possible input vectors. For example, the first codeword vector is determined by multiplying the binary channel matrix by the first possible input vector, etc. Thus, by multiplying the binary channel matrix byA respective one of the possible input vectors to determineA codeword vector.

Then, the receive combining may then be performed for selecting the codeword vector having the smallest distance to the equivalent integer representation of the digital signal. From creationA code is selected among the vectors of code words. Thus, the function for performing receive combining can be defined as:

where d (a, b) is a distance measurement of the two vectors a and b. One of ordinary skill in the art recognizes that any known (e.g., standard) distance measurement between two vectors may be used.

D.Receive combining by performing inter-stream interference cancellation

As described above, inter-stream interference cancellation is performed by: an inverse of the effective binary channel matrix is determined and a product of the inverse of the effective binary channel matrix and the equivalent integer representation of the digital signal is calculated. Then, the function for performing reception combining using inter-stream interference cancellation can be defined as:

whereinAnd isThen, x [ n ]]May be estimated to have N_rThe elements of a vector of elements. In other words, this function is given by N given below_rOne parallel channel:

wherein

It should be noted that when the data of the receive antennas is much larger than the number of transmit antennas, the receive combiner of the present disclosure significantly reduces the dimensionality of the observation while obtaining receive diversity by using a linear combiner or a simple nonlinear function. Since demodulation is performed after reception combining, the complexity of demodulation can be reduced. For example, the received combination of linear MIMO channels (or detection of data) over the finite field may take the form of matrix inversion or successive coding methods in the finite field. Matrix inversion and successive coding methods in the finite domain have less implementation complexity than that of the non-linear MIMO channel. Thus, the method of the present disclosure transforms a gaussian MIMO channel with a low resolution ADC (e.g., a 1-bit or P-stage modulo ADC) to a linear MIMO channel over a finite field, thereby reducing implementation complexity.

The following examples relate to further embodiments.

Example 1 is an apparatus for detecting data transmitted over a wireless channel, the apparatus comprising: an analog-to-digital converter (ADC) configured to, for each of a plurality of receive antennas of a receiver device, convert an analog signal received by the receive antenna into a corresponding digital signal; a channel transformer configured to channel transform the digital signal to determine a respective equivalent integer representation of the digital signal for each of the plurality of receive antennas; and a receive combiner configured to detect the data by receiving respective equivalent integer representations of the digital signals determined by combining the plurality of receive antennas.

In example 2, the subject matter of example 1, wherein the channel transformation is based on a known effective channel matrix.

In example 3, the subject matter of example 1, wherein the ADC comprises a 1-bit ADC.

In example 4, the subject matter of example 1, wherein the ADC comprises a P-level scalar quantizer.

In example 5, the subject matter of example 4, wherein the P-level scalar quantizer comprises a sawtooth transform.

In example 6, the subject matter of example 5, wherein when the P-level scalar quantizer is a sawtooth transform, the sawtooth transform is implemented by a scalar quantizer followed by a modulo operator.

In example 7, the subject matter of example 1, wherein the detected data is provided to a demodulator of the receiver device.

In example 8, the subject matter of example 1, wherein the receive combining comprises selecting a receive antenna from among a plurality of receive antennas.

In example 9, the subject matter of example 8, wherein the selected receive antennas provide subchannels with highest channel capacity.

In example 10, the subject matter of example 8, wherein the selected receive antennas are identified by determining subchannels with minimum entropy of effective noise.

In example 11, the subject matter of example 1, wherein receiving the combination comprises applying a majority decoding principle when using repetition coding on the spatial domain.

In example 12, the subject matter of example 11, wherein repetition coding in the spatial domain is used to transmit the same data to multiple receive antennas over different respective multiple subchannels.

In example 13, the subject matter of example 1, wherein receiving the combination includes detecting the data by identifying a linear block code having an equivalent integer representing a minimum distance from the digital signal.

In example 14, the subject matter of example 13, wherein the identification of the linear block code with the smallest distance is based on a known effective binary channel matrix and a known set of all possible linear block codes transmitted to the plurality of receive antennas.

In example 15, the subject matter of example 1, wherein receiving the combination includes detecting the data by performing inter-stream interference cancellation.

In example 16, the subject matter of example 15, wherein inter-stream interference cancellation is performed using an inverse of an effective binary channel matrix known by a receiver device.

In example 17, the subject matter of example 16, wherein the detecting of the data by using an inverse of an effective binary channel matrix is performed when a number of transmit antennas of the transmitter device is equal to a number of receive antennas of the receiver device.

In example 18, the subject matter of example 16, wherein the detecting of the data by using the inverse of the significant binary channel matrix is performed by selecting a number of receive antennas equal to the number of transmit antennas of the transmitter device when the number of receive antennas of the receiver device is greater than the number of transmit antennas of the transmitter device.

In example 19, the subject matter of example 1, wherein inter-stream interference cancellation is performed when the data is encoded using a series of nested linear codes.

Example 20 is a wireless device, comprising: a receive antenna array configured to receive a plurality of signals; and an apparatus for detecting data transmitted over a wireless channel according to the subject matter of example 1.

In example 21, the subject matter of example 20, wherein the wireless device is a user equipment or a base station.

Example 22 is a method for detecting data transmitted over a wireless channel, the method comprising: for each of a plurality of receive antennas, converting, by the ADC, an analog signal received by the receive antenna into a corresponding digital signal; for each of a plurality of receive antennas, channel transforming the digital signal by a channel transformer to determine a respective equivalent integer representation of the digital signal; and detecting, by the receive combiner, the data by receiving a respective equivalent integer representation of the digital signals determined by combining the plurality of receive antennas.

In example 23, the subject matter of example 22, wherein detecting data by receiving the combination comprises one of: selecting a receiving antenna from among a plurality of receiving antennas; when using repetition coding in the spatial domain, most of the decoding principles are applied; detecting data by identifying a linear block code having an equivalent integer representing a minimum distance from a digital signal; and detecting the data by performing inter-stream interference cancellation.

Example 24 is an apparatus, comprising: a processor; and a memory configured to store program instructions to be executed by the processor, wherein execution of the program instructions causes the processor to perform operations for detecting data transmitted over a wireless channel, the operations comprising: for each of a plurality of receive antennas, converting, by the ADC, an analog signal received by the receive antenna into a corresponding digital signal; for each of a plurality of receive antennas, channel transforming the digital signal by a channel transformer to determine a respective equivalent integer representation of the digital signal; and detecting, by the receive combiner, the data by receiving a respective equivalent integer representation of the digital signals determined by combining the plurality of receive antennas.

In example 25, the subject matter of example 24, wherein detecting data by receiving the combination comprises one of: selecting a receiving antenna from among a plurality of receiving antennas; when using repetition coding in the spatial domain, most of the decoding principles are applied; detecting data by identifying a linear block code having an equivalent integer representing a minimum distance from a digital signal; and detecting the data by performing inter-stream interference cancellation.

Example 26 is an apparatus for detecting data transmitted over a wireless channel, the apparatus comprising: analog-to-digital conversion means (ADC) for converting, for each of a plurality of receiving antennas of the receiver apparatus, an analog signal received by the receiving antenna into a corresponding digital signal; channel transformation means for channel transforming the digital signal to determine a corresponding equivalent integer representation of the digital signal for each of the plurality of receive antennas; and receive combining means for detecting the data by receiving respective equivalent integer representations of the digital signals determined by combining the plurality of receive antennas.

In example 27, the subject matter of example 26, wherein the channel transform is based on a known effective channel matrix.

In example 28, the subject matter of example 26, wherein the ADC comprises a 1-bit ADC.

In example 29, the subject matter of example 26, wherein the ADC comprises a P-stage scalar quantizer.

In example 30, the subject matter of example 29, wherein the P-level scalar quantizer comprises a sawtooth transform.

In example 31, the subject matter of example 30, wherein when the P-level scalar quantizer is a sawtooth transform, the sawtooth transform is implemented by a scalar quantizer followed by a modulo operator.

In example 32, the subject matter of example 26, wherein the detected data is provided to a demodulation apparatus of the receiver device.

In example 33, the subject matter of example 26, wherein the receive combining comprises selecting a receive antenna from among a plurality of receive antennas.

In example 34, the subject matter of example 33, wherein the selected receive antennas provide subchannels with highest channel capacity.

In example 35, the subject matter of example 33, wherein the selected receive antennas are identified by determining subchannels with minimum entropy of effective noise.

In example 36, the subject matter of example 26, wherein receiving the combination comprises applying a majority decoding principle when using repetition coding on the spatial domain.

In example 37, the subject matter of example 36, wherein repetition coding in the spatial domain is used to transmit the same data to multiple receive antennas over different respective multiple subchannels.

In example 38, the subject matter of example 26, wherein receiving the combination includes detecting the data by identifying a linear block code having an equivalent integer representing a minimum distance from the digital signal.

In example 39, the subject matter of example 38, wherein the identification of the linear block code with the smallest distance is based on a known effective binary channel matrix and a known set of all possible linear block codes transmitted to the plurality of receive antennas.

In example 40, the subject matter of example 26, wherein receiving the combination includes detecting the data by performing inter-stream interference cancellation.

In example 41, the subject matter of example 40, wherein inter-stream interference cancellation is performed using an inverse of an effective binary channel matrix known by a receiver device.

In example 42, the subject matter of example 41, wherein the detecting of the data by using an inverse of an effective binary channel matrix is performed when a number of transmit antennas of the transmitter device is equal to a number of receive antennas of the receiver device.

In example 42, the subject matter of example 41, wherein detecting data by using an inverse of the significant binary channel matrix is performed by selecting a number of receive antennas equal to a number of transmit antennas of the transmitter device when the number of receive antennas of the receiver device is greater than the number of transmit antennas of the transmitter device.

In example 44, the subject matter of example 26, wherein inter-stream interference cancellation is performed when the data is encoded using a series of nested linear codes.

Example 45 is a wireless device, comprising: a receive antenna array configured to receive a plurality of signals; and an apparatus for detecting data transmitted over a wireless channel according to the subject matter of example 26.

In example 46, the subject matter of example 45, wherein the wireless device is a user equipment or a base station.