Wireless communication control method, receiving station, and program

Abstract

To suppress error increase during demodulation in overloaded MIMO.SOLUTION: A wireless communication control method suppresses interference by using MMSE weight in a wireless communication environment where the number of transmitting stations for transmitting signals to a receiving station is larger than the number of receiving antennas of the receiving station. In the method, the receiving station calculates power of an interference signal in a portion where the number of transmitting stations exceeds the number of receiving antennas, which is included in signals received by the receiving unit from the transmitting stations the number of which is larger than the number of receiving antennas, calculates the MMSE weight that depends on the power of the interference signal, and uses the MMSE weight to recalculate the power of the interference signal and recalculate the MMSE weight that depends on the re-calculated power of the interference signal.SELECTED DRAWING: Figure 7

Description

[Technical Field]

[0001] The present disclosure relates to a wireless communication control method, a receiving station, and a program. [Background technology]

[0002] There is an increasing need to use terminals that can connect to public networks such as the Internet for control purposes, and there is a demand for low latency wireless communications accessing public networks. Multiple Input, Multiple Output (MIMO) is used in wireless communications. MIMO is a technology in which a base station and a terminal each use multiple antennas to communicate in the same frequency band. In addition, a MIMO technology in which multiple terminals are involved in communication simultaneously (in parallel) is called multi-user MIMO. In recent years, with the development of the Internet of Things (IoT), a rapid increase in the number of wireless terminals used for IoT is predicted, raising concerns about congestion on uplinks.

[0003] In wireless communications, a communication procedure called Configured Grant (CG) is specified. In CG, a base station transmits transmission parameters specifying the physical resources that can be used for data transmission to a terminal device in advance. The base station notifies the terminal of the start and end of permission for data transmission using CG. The terminal can transmit data to the base station using the physical resources specified for CG without negotiating with the terminal and base station before data transmission. CG is expected to be a technology that achieves low-latency communications.

[0004] In an environment where CG is used, the base station does not control the timing of terminal data transmission, so the number of signals transmitted from terminals arriving at the base station at the same time (number of transmitted signals (number of terminals): N) is limited to the number of N that can be set so that it does not exceed the number of receiving antennas (M) of the base station. A state in which the limit on N is lifted and the number of receiving antennas M exceeds the number of terminals N (N>M) is called overloaded MIMO. In an overloaded MIMO environment, there is a risk of an increase in errors during demodulation of the desired signal due to the influence of NM interfering signals that cannot be canceled even with diversity reception. The problem of an increased risk of errors during demodulation in overloaded MIMO also occurs in environments where a method other than CG with the limit on N lifted is used.

[0005] As a countermeasure against overloaded MIMO, signal separation processing using maximum likelihood detection (MLD) or a technique based on MLD has been proposed. Also, a method using spatial filtering has been proposed. [Prior art documents] [Non-patent literature]

[0006] [Non-Patent Document 1] "NR Physical Layer Specifications for 5G" NTT DOCOMO Technical Journal Vol. 26 No. 3 (Nov. 2018) [Non-patent document 2] Suzuki, "Signal Transmission Characteristics in Least-Squares Combining Diversity Reception - Relationship between Desired Signal Combining and Interference Signal Cancellation," IEICE Transactions on Electronics, Information and Communication Engineers, Vol. J75-B-II, No. 8, pp. 524-534, August 1992. [Non-patent document 3] Hayakawa, Hayashi, and Kaneko, "Low-complexity overloaded MIMO signal acceptance method using slab decoding and lattice rule reduction," IEICE Technical Report RCC2015-16, MICT2015-16, pp.77-82, May 2015. [Non-patent document 4] Higuchi and Taoka, "Multi-antenna Wireless Transmission Technology Part 3: Signal Separation Technology in MIMO Multiplexing," NTT DoCoMo Technical Journal, Vol. 14, No. 1, pp. 66-75, April 2006. Summary of the Invention [Problem to be solved by the invention]

[0007] However, there are cases where it is difficult to apply MLD, such as in systems that perform frequency domain equalization in single-carrier transmission. Also, when spatial filtering is used, preprocessing (special processing) is required, which makes the processing more complicated and cumbersome.

[0008] An object of the present disclosure is to provide a wireless communication control method, a receiving station, and a program that can suppress an increase in errors during demodulation in overloaded MIMO. [Means for solving the problem]

[0009] The present disclosure provides a wireless communication control method for suppressing interference using minimum mean square error (MMSE) weights in a wireless communication environment in which the number of transmitting stations transmitting wireless signals to a receiving station is greater than the number of receiving antennas of the receiving station. This wireless communication control method includes: calculating, by the receiving station, power of an interfering signal included in a signal received by the receiving station from transmitting stations whose number is greater than the number of receiving antennas, where the number of the transmitting stations exceeds the number of receiving antennas; calculating, by the receiving station, an MMSE weight depending on the power of the interfering signal; and recalculating, by the receiving station, the power of the interfering signal using the MMSE weight depending on the power of the interfering signal and recalculating the MMSE weight depending on the recalculated power of the interfering signal.

[0010] The present disclosure may also include a receiving station in the above-described wireless communication control method, and a program executed by a computer in the receiving station. [Effects of the Invention]

[0011] According to the disclosed embodiment, it is possible to suppress an increase in errors during demodulation in overloaded MIMO. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a wireless communication system according to an embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of the hardware configuration of a base station. [Figure 3] FIG. 3 is a diagram illustrating an example of the configuration of a terminal. [Figure 4] FIG. 4 is a diagram illustrating an example of the configuration of a base station. [Figure 5] FIG. 5 is an explanatory diagram of a case where a desired signal is diversity-received in overloaded MIMO. [Figure 6] FIG. 6 is an explanatory diagram of a case where a desired signal is diversity-received in overloaded MIMO. [Figure 7] FIG. 7 is a flowchart showing an example of a weight calculation process for MMSE diversity. [Figure 8] Figure 8 shows the definitions of the symbols used in the weight calculation. [Figure 9] FIG. 9 is a table illustrating the conditions of the simulation. [Figure 10] FIG. 10 is a diagram showing the difference in bit error rate between with and without weight calculation in a simulation. [Figure 11] FIG. 11 is a diagram showing the difference in bit error rate between with and without weight calculation in a simulation. DETAILED DESCRIPTION OF THE INVENTION

[0013] A wireless communication control method according to an embodiment suppresses interference using a minimum mean square error (MMSE) weight in a wireless communication environment in which the number of transmitting stations transmitting wireless signals to a receiving station is greater than the number of receiving antennas of the receiving station. This wireless communication control method includes the following steps. (1) The receiving station receives signals from a number of transmitting stations that is greater than the number of receiving antennas. Included is calculating the power of the interference signal where the number of transmitting stations exceeds the number of receiving antennas. (2) Calculating an MMSE weight by the receiving station that depends on the power of the interfering signal. (3) The receiving station recalculates the power of the interference signal using an MMSE weight that depends on the power of the interference signal, and recalculates the MMSE weight that depends on the recalculated power of the interference signal.

[0014] According to the radio communication control method of the embodiment, an MMSE weight that depends on (takes into account power of) the power of an interference signal in a portion where the number of transmitting stations exceeds the number of receiving antennas is calculated. In other words, according to the radio communication control method of the embodiment, an MMSE weight is calculated that takes into account power that cannot be suppressed (canceled) by using an MMSE weight obtained by a normal MMSE weight calculation method. Therefore, interference can be suppressed more effectively than suppression using a normal MMSE weight, and an increase in errors during demodulation can be suppressed.

[0015] Hereinafter, a wireless communication control method for a wireless communication system according to an embodiment, a receiving station included in the wireless communication system, and a program executed by the receiving station will be described with reference to the drawings. The configurations in the embodiments are merely examples and are not limited to the configurations of the embodiments. Figure 1 is a diagram showing an example of the configuration of a wireless communication system according to an embodiment.

[0016] In Fig. 1, the wireless communication system includes a base station 1 equipped with multiple receiving antennas, and multiple terminals 2-1, 2-2, ..., 2-N that communicate wirelessly with the base station 1. When the terminals 2-1 to 2-N are not distinguished from one another, they are referred to as "terminals 2." The base station 1 is an example of a "receiving station," and the multiple terminals 2 are examples of "transmitting stations." However, there may also be cases where terminal 2 is the receiving station and base station 1 is the transmitting station.

[0017] In the embodiment, a wireless communication system is exemplified in which, in multi-user MIMO, a terminal 2 can communicate using CG, and the number N of terminals 2 exceeds the number M of receiving antennas of a base station 1, i.e., overloaded MIMO occurs. Overloaded MIMO can be said to be a state in which a receiving station receives signals from a number of transmitting stations that exceeds the number of receiving antennas of the receiving station. Note that it is not necessarily essential that a terminal 2 be able to transmit data using CG.

[0018] The terminal 2 is called a wireless communication terminal or a wireless terminal. The terminal 2 is used, for example, to collect data for IoT and transmit the collected data to the base station 1. However, there is no limitation on the use of the terminal 2.

[0019] 2 is a diagram illustrating an example of the hardware configuration of the base station 1. In FIG. 2, the base station 1 includes a processor 11, a storage device 12, an internal interface (internal IF) 13, a network interface (network IF) 14, and a radio processing device 15.

[0020] The processor 11 is, for example, a Central Processing Unit (CPU) (Microprocessor Unit The processor 11 may be a single processor or a multiprocessor. Also, a single physical CPU connected via a single socket may have a multi-core configuration. The processor 11 may include an arithmetic unit with various circuit configurations, such as a digital signal processor (DSP) or a graphics processing unit (GPU). The processor 11 may also have a configuration in which it cooperates with at least one of an integrated circuit (IC), other digital circuit, and analog circuit. The integrated circuit includes an LSI, an application specific integrated circuit (ASIC), and a programmable logic device (PLD). The PLD includes, for example, a field-programmable gate array (FPGA). The processor 11 may also be, for example, what is called a microcontroller (MCU), a system-on-a-chip (SoC), a system LSI, or a chipset. The processor 11 is an example of a control device or a controller.

[0021] The storage device 12 is used as an area for loading a sequence of instructions (computer program) executed by the processor 11, a storage area for programs and data, a working area for the processor 11, a buffer area for communication data, and the like.

[0022] The storage device 12 includes a main storage device (called memory) and an auxiliary storage device. The main storage device is composed of random access memory (RAM) or RAM and read-only memory (ROM). The auxiliary storage device includes random access memory (RAM), hard disk (HDD), solid state drive (SSD), flash memory, and electrically erasable programmable read-only memory (EEPROM). However, the type of storage device 12 is not limited to the above.

[0023] The processor 11 executes a program stored in the memory 12, thereby operating as a device also called a baseband unit (BBU). The BBU performs encoding and modulation of data to generate a baseband signal, and the inverse process (demodulation and decoding of the baseband signal to convert the baseband signal into data). The baseband unit can also be called a control unit.

[0024] The internal IF 13 is a circuit that connects various peripheral devices to the processor 11. The network IF 14 is a communication device (circuit) that enables the base station 1 to access a network to which other base stations (base stations other than the base station 1) are connected. The network to which base stations other than the base station 1 are connected is also called a backhaul. The backhaul is, for example, a wired network using optical communication.

[0025] The radio processing device 15 includes a transceiver and a receiver, which are connected to transmitting and receiving antennas ANT-B1,...,ANT-BM via a duplexer. However, it is not essential that the antennas be used for both transmitting and receiving. When there is no need to distinguish between the antennas ANT-B1,...,ANT-BM, they will be referred to as antenna ANT.

[0026] The transceiver includes a circuit that converts a baseband signal (digital signal) into an analog signal, a circuit that converts the analog signal into a radio signal, a power amplifier that amplifies the radio signal, etc. The receiver includes a low-noise amplifier that amplifies the radio signal with low noise, a circuit that converts the radio signal into an analog signal, a circuit that converts the analog signal into a digital signal (baseband signal), etc. Radio processing device 15 may be configured to have N systems of transceivers and receivers, the same number as the number of antennas ANT.

[0027] The radio processing device 15 is called a radio device or a radio circuit because it converts baseband signals to radio signals and vice versa. The radio processing device 15 can also be configured to be remotely installed and connected to a baseband device (BBU) via a wired network using optical communication. In this case, the radio processing device 15 is called a remote radio head (RRH). Alternatively, a configuration in which multiple remote radio heads are connected to one baseband device is also possible. The network connecting the baseband device and the remote radio heads is also called a fronthaul.

[0028] FIG. 3 is a diagram showing an example of the configuration of terminal 2. In FIG. 3, radio resource blocks are illustrated along with the configuration of terminal 2. A radio resource block is a portion separated by the frequency and time axis of a subcarrier allocated to terminal 2. Radio resource blocks for communication using CG are known to terminal 2, and terminal 2 can transmit data using resource blocks for CG even without allocation of radio resource blocks by base station 1. This can be done.

[0029] In FIG. 3, a plurality of terminals 2 (2-1, . . . , 2-N) are illustrated. The detailed configuration of terminal 2 is illustrated in terminal 2-1. In the example shown in FIG. 3, each of terminals 2 has two (a pair of) antennas. For example, terminal 2-1 has antennas T-1 and T-2, and terminal 2-N has antennas T-2N-1 and T-2N. In the following description, when referring to the antennas provided in each of terminals 2-1 to 2-N without distinction, they will be referred to as "antenna T." Note that the number of antennas T provided in terminal 2 is not limited to two.

[0030] The terminal 2 is sometimes called User Equipment (UE). The terminal 2 includes a processor, memory, internal IF, and radio processing device similar to the processor 11, storage device 12, internal IF 13, and radio processing device 15 included in the base station 1, and the radio processing device is connected to an antenna T. The processor of the terminal 2 executes a program stored in the storage device, causing the terminal 2 to operate as an encoding unit 206, a modulation unit 207, and a transmit diversity processing unit 208 in radio communication processing.

[0031] The encoding unit 206 performs error correction encoding on data (transmission data) transmitted from the terminal 2. The error correction encoding may be either a soft decision code or a hard decision code, and there is no limit to the type of encoding. The modulation unit 207 digitally modulates the error correction encoded data. Examples of digital modulation methods include Quadrature Amplitude Modulation (QAM), Phase Shift Keying (PSK), and Frequency Shift Keying (FSK).

[0032] The transmit diversity processing unit 208 separates the digitally modulated signal into multiple signals to form transmit diversity branches. The transmit diversity processing unit 208 radiates the signals separated into the multiple branches from multiple antennas T via a radio processing device. In the example of Fig. 3, each transmit diversity processing unit 208 of the terminal 2 separates the transmission path using two antennas to form transmit diversity branches.

[0033] A Reference Signal (RS) is added to each of the separated signals. The RS is generally called a pilot signal and is a signal known to the base station 1. By transmitting a different RS for each terminal, the base station 2 can identify the transmitting terminal 2 by referring to the RS. Note that although the terminal 2 performs transmit diversity using the transmit diversity processing unit 208, transmit diversity is not essential, and for example, the terminal 2 may be configured to use one antenna for transmission and not perform transmit diversity. Furthermore, the number of signal sequences separated by transmit diversity may be two or more depending on the number of antennas.

[0034] Fig. 4 shows an example of the configuration of the base station 1. The base station 1 operates as a device that performs the processing shown in Fig. 4 by the processor 11 executing a program stored in the storage device 12. That is, the base station 1 operates as a device including a replica removal unit 101, a diversity reception and equalization processing unit 102, a demodulation unit 103, a decoding unit 104, and a replica generation unit 105. Furthermore, the replica generation unit 105 operates as a device including an encoding unit 106, a modulation unit 107, a transmit diversity processing unit 108, and a channel matrix multiplication unit 109.

[0035] In the base station 1, an RS is extracted from each of the signals received by M antennas ANT (ANT-B1 to ANT-BM). The RS is used to identify the terminal 2 and to estimate the channel of the signal from the terminal 2. The receive diversity and equalization processing unit 102 performs receive diversity and equalization using minimum mean square error (MMSE). That is, the receive diversity and equalization processing unit 102 generates a channel matrix from a channel estimation value using the RS of the desired signal, and calculates an MMSE weight for each transmit antenna branch from the channel matrix to suppress interference from other transmit antenna branches. Furthermore, the receive diversity and equalization processing unit 10 2 multiplies the received signal vector by the MMSE weight matrix to obtain an equalized signal with interference suppression.

[0036] Demodulation section 103 calculates a log likelihood ratio (LLR) for each bit from the squared Euclidean distance between the equalized signal and the transmission signal point replica. Decoding section 104 performs error correction decoding using the LLR to decode the data.

[0037] The replica generation unit 105 performs processing to generate a replica of the desired signal from the data obtained by the decoding unit 104. That is, the replica generation unit 105 generates a replica of the desired signal using an encoding unit 106, a modulation unit 107, a transmit diversity processing unit 108, and a channel matrix multiplication unit 109. The replica removal unit 101 uses the replica to remove the desired signal from the signal received by the base station 1. This is called a SIC (Successive Interference Canceller) loop, and by removing a successfully demodulated and decoded signal (interference replica of the transmitted signal) from the incoming signal (received signal), it is possible to reduce interference signals with the desired signal. Note that in this embodiment, the base station 1 selects desired signals from signals received by N terminals 2 in order of best signal-to-interference ratio (SIR). However, the desired signals may be selected in an order other than SIR order.

[0038] 5 and 6 show the state of overloaded MIMO. In overloaded MIMO, signals arrive at the base station 1 from N terminals 2, which is greater than the number M of receiving antennas of the base station 1. The channel matrix H in this case can be expressed by the following equation (1).

number

[0039] The channel matrix H is a matrix that indicates the amount of fluctuation in amplitude and phase of the transmission path between the antennas T-1 to TN of the terminal 2 and the antennas ANT-B1 to ANT-BM of the base station 1. The channel matrix H is determined by receiving the RS transmitted from the antennas 2j-1, 2j (j=1, . . . , N) of each terminal 2 at each antenna ANT-B1 to ANT-BM. The same applies when the number of antennas of the terminal 2 is different from 2. In short, the amount of fluctuation corresponding to the transfer function of the transmission path is obtained by the reference signal transmitted and received between the antennas 2j-1, 2j on the transmitting side and the antenna ANT-Bi on the receiving side. h in the channel matrix H m,n denotes a channel estimation value transmitted from the n-th terminal among the multiple terminals 2 and received by the m-th antenna ATN of the base station 1.

[0040] Furthermore, the channel matrix H is a matrix that indicates the amount of fluctuation in amplitude and phase of the transmission path between each antenna T of the terminal 2 and the receiving antennas ANT-B1 to ANT-BM of the base station 1. By multiplying the transmission signal vector of each antenna T of the terminal 2 by the channel matrix H, it is possible to obtain an estimate of the received signal vector at the receiving antennas ANT-B1 to ANT-BM of the base station.

[0041] In this embodiment, the RSs are orthogonal to prevent interference between multiple terminals 2. Because the RSs are orthogonal, the base station 1 can estimate the channel matrix H from the RSs even in an overloaded MIMO state.

[0042] In overloaded MIMO, the number N of terminals 2 exceeds the number M of receive antennas. If one of the signals of the N terminals (for example, the signal of terminal 2-1) is the desired signal (indicated by the bold arrow in FIGS. 5 and 6), the M-1 portion of the signals (signals of terminals 2-2 to 2-M) will be suppressed (canceled) by the MMSE method (indicated by the dashed arrow in FIGS. 5 and 6). The NM portion of the signals (signals of terminals 2-M+1 to 2-N) will not be suppressed (canceled) by the MMSE method (indicated by the dashed arrow in FIGS. 5 and 6).

[0043] From this, the channel matrix H is the transmission path vector h1 of the desired signal and the transmission path vector (channel matrix) H' of the signal to be cancelled. C The transmission path vector (channel matrix) H C (H C =[h1,H' C ]) and the transmission path vector (channel matrix) H of the signal that is not canceled u The transmission line vector H C The matrix of can be expressed by the following equation (2), the transmission path vector of the desired signal h1 can be expressed by the following equation (3), and the transmission path vector H'c can be expressed by the following equation (4).

number

[0044] In addition, the transmission path vector (channel matrix) of the signal that is not canceled is H u is expressed by the following equation (5).

number

[0045] In the normal MMSE method, the signal of the part of "M-1" which is the number of receiving antennas M minus 1 is The MMSE weights for suppressing (canceling) the interference signals are calculated. However, in overloaded MIMO, the signals in the "NM" portion, which is the number of terminals 2 minus the number of antennas M, are not suppressed (canceled). Therefore, MMSE equalization using the conventional MMSE method may increase the error rate during demodulation.

[0046] In this embodiment, the receive diversity and equalization processing unit 102 determines the weight of the MMSE diversity (MMSE weight W mmse ) is calculated to suppress the increase in the error rate during demodulation.

[0047] 7 is a flowchart showing an example of a process of calculating weights for MMSE diversity, which is executed by (the processor 11 operating as) the receive diversity and equalization processing unit 102. FIG. 8 shows definitions of symbols and the like used in the weight calculation shown in FIG.

[0048] In step S21, the processor 11 uses the zero-forcing method (ZF method) to calculate a weight W to remove the interference signal (the signal in the "M-1" part) that is to be canceled by the receive diversity. zf Calculate the weight W zf The calculation formula for R is shown in the block of step S21. C is a transmission path vector obtained by multiplying the transmission amplitude p of the desired signal and the signal to be cancelled, and r1 is a propagation path vector obtained by multiplying the transmission amplitude p of the desired signal. T " indicates a transposed matrix, and the symbol " * " indicates the complex conjugate. r1 can be expressed by the following formula (6), and R C can be expressed by the following equation (7). Note that the signal with the best SIR is selected as the first desired signal, for example, from among the signals of terminal 2 identified by RS. However, the order in which desired signals are selected is not limited to the order of best SIR.

number

[0049] In step S22, processor 11 determines the weight W zf The normalized weight W' zf The normalization formula is as shown in the block of step S22. In step S23, the processor 11 calculates the weight W zf R u Interference signal vector G multiplied by u Calculate G u The calculation formula for R is shown in the block of step S23. u is a channel matrix obtained by multiplying a signal that is not canceled by receive diversity (interference signal in the "NM" part) by a transmission amplitude p, and can be expressed by the following equation (8).

number

[0050] In step S24, the processor 11 calculates the interference signal vector G u The sum of the power (interference power) P u Calculate P u The calculation formula for P is as shown in the block of step S24. u is the power of the signals of terminals 2-M+1 to 2-N that are not cancelled, as shown in FIG. 6, that is, p m+1 2 ,···,p N 2 In the calculation formula, the power consumption per device is calculated as 1.

[0051] In step S25, the processor 11 calculates the weight W mmse Calculate W mmse The calculation formula for is as shown in the block of step S25. In the normal weight calculation formula, P n , that is, the noise power per receiving antenna is taken into consideration. In this embodiment, P n In addition to the above, the power P of the interference signal that is not canceled by receive diversity (the portion where the number N of terminals 2 exceeds the number M of receive antennas) u Therefore, the signal from the terminal 2 can be suppressed as an interference signal.

[0052] The MMSE weight W shown in the block of step S25 mmse In the calculation formula, W mmse The value of the power P of terminal 2 of NM u Therefore, in step S26, the processor 11 determines the current W mmse The value of W zf Then, the process returns to step S22. As a result, a new W mmse In this embodiment, the value of W calculated for the second time is calculated (updated). mmseThe value of is used for multiplication to suppress the interference signal.

[0053] Thereafter, the replica of the desired signal h1 is used to remove the desired signal h1 from the incoming signal by the replica generation unit 105 and the replica removal unit 102. Then, the next desired signal h2 is selected, and the weight W mmse The interference signal is suppressed using R. Such processing related to the SIC loop is repeated. Note that in a situation where there is no overloaded MIMO, that is, when the number N of terminals 2 is equal to or less than the number M of receiving antennas, R u Since there is no power P u is not calculated, and the weights are calculated using the normal MMSE method.

[0054] In the process shown in FIG. 7, the power P u To obtain the initial value of W zf However, the usual MMSE weight calculation formula (W = (R c * R c T +(P n )I) -1 r1 * ) calculation result to W zf may be used instead of

[0055] 9 to 11 show examples of simulation results based on the processing of this embodiment. Fig. 9 shows examples of simulation conditions. This simulation is performed when the number of simultaneous transmission terminals is 3 to 6 (each terminal 2 has two transmission antennas) and when the number of simultaneous transmission terminals is 5 to 10 (each terminal 2 has four transmission antennas).

[0056] The transmission data size is 80 bits. The error correction code is turbo code (coding rate 1 / 3). The modulation method is single-carrier QPSK. The transmission path is A single-path Rayleigh fading of several tens of hertz was assumed, and the signal-to-noise ratio (SIR) of the transmission path was assumed to be 30 dB.

[0057] FIG. 10 illustrates the difference in bit error rate in the first SIC run when a normal MMSE weight calculation method is used and when the MMSE weight calculation method of this embodiment (proposed) is used in a simulation. The example shown in FIG. 10 shows a case where the number of receiving antennas at the receiving station (base station) is two and the number of terminals is three (when the number of terminals exceeding the number of receiving antennas is one (NM=1)). Each graph in FIG. 10 shows an example without transmit diversity. In FIG. 10, the horizontal axis of the graph represents SIR (dB) and the vertical axis represents the bit error rate. Also, in FIG. 10, the upper graph shows a case where the normal MMSE weight calculation method is used, and the lower graph shows a case where the proposed MMSE weight calculation method is used. The example shown in FIG. 11 shows a case where the number of receiving antennas is four and the number of terminals is five (when the number of terminals exceeding the number of receiving antennas is one).

[0058] As shown in Figures 10 and 11, it was found that applying the proposed MMSE weight calculation method showed a better bit error rate regardless of the SIR value, that is, it was found that it was possible to suppress interference and reduce the bit error rate compared to the conventional MMSE weight calculation method.

[0059] As described above, according to the wireless communication system (wireless communication control method) according to the embodiment, when interference is suppressed by MMSE diversity (MMSE equalization is performed) in overloaded MIMO, the power P u is calculated (step S24). u is the interference signal vector G corresponding to the NM part u The power P u The MMSE weight W depends on mmse is calculated (step S25).

[0060] In this embodiment, the power P uTo obtain the initial value of , the initial value of the MMSE weight is set. The initial value of the MMSE weight is calculated by dividing the transmission amplitude p of the signal of terminal 2 corresponding to the part of the number (M-1) that is 1 less than the number of transmitting terminals and receiving antennas M of the desired signal by the channel matrix H c Matrix R multiplied by c Using the weight W zf can be obtained by calculating using the zero-forcing method (step S21). However, the initial value of the weight may be obtained by a calculation method (normal calculation method of the MMSE weight) for the part of the number (M-1) that is 1 less than the number M of transmitting terminals and receiving antennas of the desired signal (desired signal for the first SIC).

[0061] Power P u Using the initial value of power P u The MMSE weight W depends on mmse When it is found (step S25), the value is set as the initial value of the MMSE weight (step S26), and the power P u (Step S24). This results in a more appropriate weight W mmse is calculated and multiplied by the channel matrix of the desired signal. This makes it possible to appropriately suppress interference in overloaded MIMO and reduce the error rate during demodulation (see FIGS. 10 and 11).

[0062] Calculated P u The value of can be used to calculate the log-likelihood ratio (LLR) required for decoding the error correction code during demodulation, and P u The error rate after error correction can be reduced compared to when the error correction method is not used.

[0063] In this embodiment, the signal with the best SIR among the signals of the N terminals is identified as the first desired signal by the SIC method, and the MMSE equalization result for this desired signal is output from the receive diversity and equalization processing unit 102 and used for demodulation and decoding. Then, a replica of the first desired signal is generated, and the replica is used to select the first desired signal from the N signals that have arrived. The calculation of the MMSE weight according to this embodiment is applicable to all of the second and subsequent desired signals.

[0064] However, the MMSE weight calculation method according to the present embodiment can also be applied to a normal MMSE method other than the SIC method, i.e., when the MMSE equalization results for each transmission signal are calculated in parallel. Furthermore, the cause of overloaded MIMO is not limited to the use of CG. Furthermore, the MMSE weight calculation method according to the present embodiment can also be applied when the number N of terminals receiving signals from one terminal (transmitting station) exceeds the number M of receiving antennas at the receiving station. The configurations of the embodiments are merely examples, and the configurations described in the embodiments can be modified as appropriate without departing from the spirit of the present disclosure. [Explanation of symbols]

[0065] 1 base station 2. Terminal 11 processors 12 Memory 13 Internal Interface 14 Network Interface 15 Radio processing unit 101 Replica Removal Section 102 Diversity and equalization processing section 103 Demodulation section 104 Decoding unit 105 Replica Generation Unit 106 Encoding section 107 Modulation section 108 Transmission diversity processing unit 109 Channel Processing Unit ANT antenna

Claims

1. A wireless communication control method for suppressing interference using minimum mean square error (MMSE) weights in a wireless communication environment in which the number of transmitting stations that transmit wireless signals to a receiving station is greater than the number of receiving antennas of the receiving station, comprising: calculating, by the receiving station, power of a portion of an interference signal included in signals received by the receiving station from transmitting stations whose number is greater than the number of receiving antennas, where the number of the transmitting stations exceeds the number of receiving antennas; calculating, by the receiving station, an MMSE weight that depends on the power of the interfering signal; recalculating, by the receiving station, the power of the interfering signal using an MMSE weight that depends on the power of the interfering signal, and recalculating an MMSE weight that depends on the recalculated power of the interfering signal; Including, A wireless communication control method, wherein in calculating the power of the interference signal, an initial value of the power of the interference signal is calculated by multiplying a channel matrix of the interference signal multiplied by a transmission amplitude by an initial value of an MMSE weight.

2. 2. The wireless communication control method according to claim 1, wherein in calculating the power of the interference signal, the receiving station calculates the initial value of the MMSE weight using a zero-forcing method.

3. A receiving station that has a plurality of receiving antennas and suppresses interference using a minimum mean square error (MMSE) weight in an environment where a number of transmitting stations that transmit wireless signals is greater than the number of the plurality of receiving antennas, comprising: A control device that executes the following: calculating power of an interference signal included in a signal received by the receiving station from a number of transmitting stations greater than the number of receiving antennas, for a portion where the number of the transmitting stations exceeds the number of the receiving antennas; calculating an MMSE weight depending on the power of the interference signal; recalculating the power of the interference signal using the MMSE weight depending on the power of the interference signal; and recalculating the MMSE weight depending on the recalculated power of the interference signal. Including placement, The control device calculates an initial value of the power of the interference signal by multiplying the channel matrix of the interference signal multiplied by the transmission amplitude by an initial value of an MMSE weight. Receiving station.

4. The control device calculates the initial value of the MMSE weight using a zero-forcing method in calculating the power of the interference signal.

4. A receiving station according to claim 3.

5. In an environment in which the number of transmitting stations that transmit wireless signals exceeds the number of the plurality of receiving antennas, a computer in a receiving station that suppresses interference using a minimum mean square error (MMSE) weighting comprises: Calculating the power of a portion of interference signals included in signals received by the receiving station from a number of transmitting stations greater than the number of receiving antennas, where the number of the transmitting stations exceeds the number of the receiving antennas; calculating an MMSE weight that depends on the power of the interfering signal; recalculating the power of the interfering signal using an MMSE weight that depends on the power of the interfering signal, and recalculating the MMSE weight that depends on the recalculated power of the interfering signal; In calculating the power of the interference signal, the computer is caused to execute a process of calculating an initial value of the power of the interference signal by multiplying the channel matrix of the interference signal multiplied by the transmission amplitude by an initial value of an MMSE weight. program.

6. In calculating the power of the interference signal, the computer is caused to execute a process of calculating an initial value of the MMSE weight using a zero-forcing method. The program according to claim 5.

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