Anti-interference communication method on multi-antenna wireless channel

Abstract

The invention relates to the field of wireless communication, in particular to an anti-interference communication method and device on a multi-antenna scattering channel. Comprising the following steps: receiving a pure interference signal by a protocol, generating an interference eliminator by the pure interference signal, carrying out interference elimination before communication signal detection, filtering before ball detection, and selecting a part of detected information as noise before ball detection. According to the anti-interference wireless communication mode, the interference signal forming mode of an interference party does not need to be known, and communication can be achieved under the interference conditions of ultra-strong same carrier frequency, same information transmission time slot and same code pattern.

Description

Technical Field

[0001] The present invention proposes an anti-interference communication method on a multi-antenna wireless channel. By using the method, wireless communication can be achieved even in the case of non-protocol interference. Technical Background

[0002] Wireless spectrum is a finite resource. As wireless communication applications expand, the need to address this resource constraint, such as wireless spectrum, and to enable communication in the presence of wireless interference, is becoming a viable approach.

[0003] Interference in wireless communications can be categorized as either protocol-based or non-protocol-based interference. Protocol-based interference occurs when the wireless communication system knows the relevant technical parameters of the interfering party, such as carrier frequency, modulation method, signal waveform and power, channel coding and decoding methods used, and channel information. In the case of protocol-based interference, the technical parameters of the interfering party can be used to estimate the interference and then eliminate it, enabling wireless communication. Numerous research results have been published on interference elimination. Non-protocol-based interference occurs when the wireless communication system is unaware of the interfering party's technical parameters. In this case, the only means of determining and estimating the interfering party's electromagnetic characteristics, such as the spectrum and field strength distribution, is to detect and estimate the interference. This makes it difficult to mitigate the interference during communication.

[0004] The present invention proposes an anti-interference communication method on a multi-antenna wireless channel. Using this method, communication can be achieved without having an agreement with the interfering party.

[0005] Spatial modulation is a technology that is often discussed on multi-antenna scattering channels. For the uplink channel, the main discussion is about its receiving technology, mainly for the case where the receiving antennas and transmitting antennas are equal or the number of receiving antennas is greater than the transmitting antennas. Using more receiving antennas can achieve lower complexity and more diversity gain. For the downlink channel, the commonly used technology is closed-loop transmission technology. Closed-loop technology requires knowing the channel information at the transmitting end and designing the precoding of spatial modulation at the transmitting end. Spatial modulation cannot obtain transmit diversity gain. In the present invention, we use spherical soft detection technology for random space-time diffusion systems. It is an open-loop technology that is applicable to both uplink and downlink channels. It does not require knowing the channel information at the transmitting end. If the number of transmitting antennas is large and greater than the receiving antennas, it can reduce the detection complexity and obtain transmit diversity gain.

[0006] As noise increases and the signal space shrinks, the signal detector has a significant impact on its bit error rate performance. The maximum a posteriori probability (MAP) detector has the best bit error rate performance, but also has an exponentially increasing computational complexity. Therefore, the MAP detector is not suitable for practical applications, especially for scenarios where a large number of bits need to be detected. There is a lot of research work trying to reduce the computational complexity with minimal loss of bit error rate performance. The sphere detector or sphere decoder searches for a list of signal sequences containing the minimum distance signal within the range of a multidimensional signal sphere, rather than searching for the signal that can achieve the minimum distance within the range of all signal sequences. Because it can search for the shortest distance signal, the bit error rate performance of the sphere detector can reach the performance of the maximum likelihood detector, or can approach the performance of the MAP signal detector.

[0007] There are several ways to improve sphere decoding or sphere detectors, such as finding the best K points in each layer, choosing the appropriate sphere radius, preprocessing the signal, or properly sorting the processing order. The complexity of a sphere decoder or sphere detector can be defined as the number of signal points within the sphere, or the average of the number. If the signal points are random, the number of signal points within the sphere is also random. This means that the sphere decoder or sphere detector requires a lot of memory. If spatial modulation is used in a MIMO system, the complexity of the sphere detector decreases as the number of receiving antennas increases. For random grid point signals, signal preprocessing or adjusting the signal order does not change the complexity distribution.

[0008] Another approach to reducing the complexity of the sphere detector is to reduce its signal dimensionality. This can be achieved by equating part of the signal to normally distributed noise. This approach has been applied in previous sphere detectors, such as the SUMIS detector and the MSE soft detector. In this paper, we propose a sphere soft detector that uses a Gaussian approximation for part of the interfering signal and apply this detector to random space-time diffusion systems. The soft detector uses a prior probability to detect the signal. This allows us to calculate the signal-to-interference ratio (SIR) of each signal using the prior probability. We then select signals with low SIRs to form a subset. This interference is approximated as Gaussian noise. The sphere detector of this invention searches for signals within the complement of this subset. If the complement contains only the desired signal or all signals, the sphere soft detector of this invention becomes an MMSE soft detector or a MAP soft detector, respectively. Soft detectors are typically implemented using a recursive loop. As the loop is repeated more times, the prior probability of the signal becomes increasingly better, reducing the signal dimensionality of the sphere detector, reducing its complexity, and improving its performance.

[0009] In this invention, multiple antennas and antenna arrays have different meanings. Each antenna in an antenna array has specific positioning requirements to ensure that the received signals from each antenna maintain a certain phase relationship. In this invention, multiple antennas only require that the antennas be sufficiently spaced apart. The received signals from each antenna are affected by radio wave scattering and reflection, and therefore have a certain degree of phase independence. Summary of the Invention

[0010] Considering communication over a multi-antenna wireless channel, the transmitter uses randomized space-time spreading (see the inventor's paper [1]), and the signal received by the receiver can be modeled using the following mathematical formula:

[0011]

[0012] where N r The matrix Y is the received signal matrix, and H is the N r ×N t The channel coefficient matrix, N t ×N matrix S k The sender sends bit b k The diffusion matrix used has K bits diffused simultaneously, W is the random vector composed of noise interference signals on each receiving antenna, N r is the number of antennas at the receiving end, N t is the number of transmitting antennas, and N is the system's diffusion factor in the time domain. t Segment constitutes the diffusion matrix S k 【1】.

[0013] The communication system receives an interference signal from an interference source with multiple antennas. A filter F is used to reduce the interference of the received signal. We call F a projection filter. 2 = F. The noise and interference that cannot be eliminated are approximated as random variables, as shown in the following formula.

[0014]

[0015] The transmitter sends a suitable training chip vector, where the number of training chips is greater than the number of receiving antennas, so that an estimated value of Z can be obtained.

[0016] Spread spectrum and diffusion communication signal transmission and reception methods can also be used in radar signal detection, positioning systems, navigation systems, etc. Therefore, the method of using projection filters to eliminate interference in (14) can also be used to eliminate interference in multi-antenna radar signals, multi-antenna positioning signals, and multi-antenna navigation signals. Other communication systems using multiple antennas, such as spatial modulation, can also use projection filters to reduce and eliminate interference.

[0017] For formula (2), it is more convenient to vectorize each matrix. Let r = Vec[Y f ],w=Vec[W fz ],and

[0018]

[0019] In this way, there When detecting the k-th bit signal, the other signals are divided into two subsets G k , g k , then r can be expressed as

[0020]

[0021] Bundle Each element in is approximately a normally distributed random variable, and Considered as a noise term, its variance matrix is E[b i ] can be obtained by calculating its prior probability. From this we can calculate the posterior log-likelihood ratio (LLR) of signal k as

[0022]

[0023] The summation of the exponential functions in the numerator and denominator of the first term can be approximated by their maximum values ​​or by partial summation including the maximum value. Therefore, the signal sequence can be searched within a sphere with a radius of ρ, that is, the b that satisfies the following formula can be obtained. i , i∈G k ,

[0024]

[0025] Here we use the signal's prior LLR to determine the sphere radius, taking

[0026]

[0027] Then there is

[0028]

[0029] right Perform Cholesky decomposition, get

[0030]

[0031] Then perform QR decomposition on , have

[0032]

[0033] here For i<|G k |, yes

[0034]

[0035] In this way, we can get k′=|G k |-1 to 0 list A list of . LLRs are calculated from this list.

[0036] Using prior LLR, detect b k The energy ratio of interference noise and signal is

[0037]

[0038] Select bits with less interference to form g k The size of the interference is determined by formula (12) so that the interference-signal ratio of formula (11) reaches a smaller value.

[0039]

[0040] Technical effects: 1) Communication can be achieved even in the presence of extremely strong interference with the same carrier frequency, the same information transmission time slot, and the same code type; 2) The anti-interference wireless communication method of the present invention does not require knowledge of the interference signal formation method of the interfering party; 3) The information transmission rate is relatively high; 4) Transmission diversity gain can be obtained, and the information transmission quality is good.

[0041] References:

[0042] 【1】Dianjun Chen, "A Randomized Space-Time Spreading Scheme for MassiveMIMO Channels," IEEE Trans.Wireless Commu.Vol.15, No.5, May 2016, pp.3668-3678. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] none DETAILED DESCRIPTION

[0044] The system is described above. Some specific technical issues and their implementation solutions are as follows.

[0045] 1. A way to obtain pure interference vector signal:

[0046] During the coherence time of the channel, several frames of signals can be sent. Before these frames are sent, the transmitter sends multiple zero signals, and the number of chips contained in the zero signals is greater than or equal to the number of receiving antennas. At this time, the receiver captures and receives multiple interference and noise signals.

[0047]

[0048] in is the N of the captured i-th chip r ×1 interference, noise vector signal. Ignoring the noise, we say that the vector in (13) consists of pure interference signals.

[0049] 2. A method for generating a projection filter:

[0050] Generate the matrix Y using the following steps z , where Y z(*，j) is the matrix Y z The jth column of N r ×N r The unit diagonal matrix of , the matrix symbol with a "+" superscript indicates its generalized inverse matrix (pseudonym inverse matrix), such as It's Y z The generalized inverse matrix of .

[0051] 1)

[0052] 2)

[0053] …;

[0054] j+1)

[0055] …

[0056] The termination condition of the generation step: If there is Less than tens of times the noise energy (the specific multiple can be determined by testing, 1 to 2 orders of magnitude can be considered), or N has been generated r -1 Y z The column vector of is generated. At this time, the matrix Y z The number of columns is N i .

[0057] Use Y z Generate a projection filter, which we call the interference kernel projection filter, as follows

[0058]

[0059] The interference kernel projection filter (14) can be used in equation (2).

[0060] For example, when the interferer has only one antenna, it can use only one chip of interference noise signal. At this time, the interference kernel projection filter is

[0061]

[0062] 3. Search for the operating carrier frequency band:

[0063] The random space-time diffusion system can search for frequency bands with less interference to improve communication quality. The search method is as follows.

[0064] 1) Using coherent operating frequencies as intervals, within the communication frequency band that ensures a certain degree of independence of the received signals of multiple antennas, use multiple antennas to simultaneously receive interference signals of multiple carrier frequencies;

[0065] 2) Use chip matched filters at each carrier frequency to generate their own Y z , get their own N i .

[0066] 3) Select the one with the smallest N i The carrier frequency is used as the working frequency for anti-interference communication.

Claims

1. In random space-time diffusion communication systems, a projection filter F is used to reduce interference before signal processing at the receiver. It can also be used in other multi-antenna systems, such as spatial modulation, radar, positioning, and navigation.

2. As shown in formula (8) in the patent specification, the signal of the ball detection is processed using the matrix before detection. Perform filtering.

3. Use bit signals with less interference to form g k The size of the interference is determined by formula (12), so that the signal detection has a smaller interference-to-signal ratio.

4. As shown in Specific Implementation 1, a zero chip signal is sent, multiple interference and noise signals are received, and the projection filter F is generated using them.

5. Matrix Y in Specific Implementation 2 z The generation steps of: step 1); step 2); ...; step j+1); .... The termination condition of the generation step.

6. The interference kernel projection filter in Specific Implementation 2 is formula (14) in the patent specification.

7. Interference kernel projection filter when the number of interference antennas is 1, that is, formula (15) in the patent specification.

8. In the specific embodiment 3, the key step of the search method for the working carrier frequency band is to select the carrier with the minimum N i The carrier frequency is used as the working frequency for anti-interference communication.

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