Performance optimization method of CR-NOMA communication system based on multi-user scenario

Abstract

The present invention relates to a CR-NOMA system performance optimization method based on a multi-user scenario, which belongs to the field of wireless mobile communications. In the t1 time slot, SS sends a superposition signal X(t1) to a full-duplex relay R and a first secondary user D0; R decodes the received signal of the t1 time slot to obtain D0, D1, ..., D M The desired signal is re-encoded as x0(t1), x1(t1), x2(t1), ...., x M (t1); t2 time slot, SS sends the superposition code X(t2) to R and D1, and R sends the coded signal to R and secondary users D0, D1, :.:, D M , D0 performs maximum ratio combining on the received signal and decodes the signal y0(t2), D m (m∈{1, 2, ..., M}) decodes the received signal y m (t2); According to Shannon's formula, calculate D0 and D m The achievable rate of (m∈{1, 2, ..., M}) is determined, and based on the definition of the interruption probability, the user interruption probability is calculated; based on the optimal power allocation for the near-end users, the total achievable rate of the system is maximized.

Description

Technical Field

[0001] The invention belongs to the field of wireless mobile communications, and relates to cognitive radio spectrum sensing technology and non-orthogonal multiple access technology. Background Art

[0002] The rapid development of wireless communication technology in recent years has increased the demand for spectrum resources, and the inefficient use of many authorized frequency bands has further highlighted that spectrum scarcity has become one of the current problems that need to be solved urgently. Cognitive radio CR technology can effectively alleviate the contradiction between static spectrum allocation strategy and dynamic spectrum demand. By real-time monitoring of the occupation of authorized users in the authorized frequency band, secondary users can opportunistically access the authorized frequency band for communication without causing interference to PU, thereby improving spectrum efficiency. Users of the non-orthogonal multiple access NOMA system receive superimposed signals and use serial interference cancellation SIC technology to obtain their own signals. Although the implementation complexity of the user receiver is higher than that of orthogonal multiple access OMA, higher spectrum efficiency can be obtained, which reflects the idea of ​​NOMA technology to exchange receiver complexity for improved spectrum efficiency. In order to further improve spectrum efficiency, CR technology is introduced into NOMA (CR-NOMA), and secondary users dynamically obtain authorized spectrum access opportunities, and the overall throughput of the system is improved.

[0003] Cooperative communication technology is an effective technology to combat path loss, channel fading and shadowing effects. It can effectively increase the communication coverage area and improve the service quality of users. In a cooperative communication system, by using relay nodes to forward the signals of source nodes, a spatial diversity gain similar to that of a MIMO system can be obtained, which is called cooperative diversity. The working modes of relay nodes can be divided into full-duplex mode and half-duplex mode. When the relay node adopts half-duplex mode, the relay node can only be limited to orthogonal channels when receiving and sending, which makes the spectrum utilization efficiency low. When the relay node adopts full-duplex mode, the relay node only needs one end-to-end channel for transmission, so that the full-duplex cooperative protocol can obtain higher capacity performance than the half-duplex cooperative protocol. However, since the relay node is in full-duplex mode, the node with only one receiving antenna receives signals from the relay link and the direct link at the same time under ideal conditions, which interferes with the near-end user and reduces the communication quality of the near-end user. Therefore, when the communication quality of the far-end user is improved, the communication quality of the near-end user is reduced. The industry has always focused on the transmission rate and service quality of edge users, but ignored the communication quality of near-end users.

[0004] In summary, the problems existing in the prior art are: the spectrum efficiency needs to be further improved, and the communication quality of both near-end users and far-end users in the traditional NOMA relay system is difficult to ensure at the same time.

[0005] The difficulty of solving the above problems: While improving the communication quality of remote users, it is necessary to ensure that the impact on near-end users is small and to ensure the improvement of the overall system performance.

[0006] The significance of solving the above technical problems: Combining CR, NOMA and full-duplex technologies, while ensuring user fairness, maximizes the total achievable rate of the system, and can improve the total achievable rate and spectrum efficiency of the system. Summary of the invention

[0007] In view of the problems existing in the prior art, the present invention provides a CR-NOMA communication system performance optimization method based on a multi-user scenario, which is used to improve the spectrum efficiency and improve the communication quality of near-end and far-end users.

[0008] In order to achieve the above object, the present invention provides the following technical solutions:

[0009] In a first aspect, a CR-NOMA communication system performance optimization method based on direct transmission and full-duplex relay is provided, which specifically includes the following steps:

[0010] S201: In time slot t1, SS sends a superimposed signal X(t1) to the full-duplex relay R and the first secondary user D0;

[0011] S202: R decodes the received signal of time slot t1 to obtain D0, D1, ..., D M The desired signal is re-encoded as x0(t1), x1(t1), x2(t1), ...., x M At time slots (t1) and t2, SS sends the superposition code X(t2) to R and D1, and R sends the coded signal to R and secondary users D0, D1, ..., D M ;

[0012] S203: D0 performs maximum ratio combining on the received signal and decodes the signal y0(t2), D m (m∈{1, 2, ..., M}) decodes the received signal y m (t2);

[0013] S204: Calculate D0 and D according to Shannon's formula m The achievable rate of (m∈{1, 2, …, M}) and the user interruption probability are calculated based on the interruption probability definition;

[0014] S205: Maximizing the total achievable rate of the system based on optimal power allocation to the near-end user.

[0015] Furthermore, the SS and R in the first and second steps allow secondary communication only when the PD is not interfered by the SN. Therefore, the interference temperature limit T ITCAs shown below

[0016]

[0017] in and Represent the maximum transmit power of SS and R respectively; is the channel coefficient between SS and PD; is the channel coefficient between R and PD.

[0018] Furthermore, in the second step, R adopts full-duplex mode, and the self-interference is Where P R is the transmit power of R, β m Yes D m The power allocation factor.

[0019] Furthermore, in the third step, D1 uses irrational self-interference elimination, and the residual interference received by D1 is f R0 X M (ta), where 0≤ξ≤1.

[0020] Furthermore, in the fourth step, D0, D1, ..., D M The interruption probability is or When D0, D1, ..., D M The interruption probability is equal to 1, where R m Indicates D m target rate.

[0021] Furthermore, the function for maximizing the total achievable speed of the system in the fifth step is a piecewise function and the objective function contains multivariable factors, so the KKT method cannot be directly applied to this model to obtain the optimal system performance optimization method. Therefore, it is considered to solve it based on the exhaustive search algorithm.

[0022] In a second aspect, the present application provides an electronic device, comprising: a processor and a memory, wherein the memory is coupled to the processor, the memory is used to store computer program code, the computer program code comprises computer instructions, and when the processor reads the computer instructions from the memory, the electronic device executes the CR-NOMA communication system performance optimization method as described in the first aspect.

[0023] In a third aspect, the present application provides a computer storage medium comprising computer instructions. When the computer instructions are executed on a terminal, the terminal executes the CR-NOMA communication system performance optimization method as described in the first aspect.

[0024] In a fourth aspect, the present application provides a computer program product. When the computer program product is run on a computer, the computer executes the CR-NOMA communication system performance optimization method as described in the first aspect.

[0025] Another object of the present invention is to provide a wireless mobile communication system with a CR-NOMA communication system performance optimization method based on direct transmission and full-duplex relay.

[0026] In summary, the advantages and positive effects of the present invention are as follows: the present invention introduces CR into the NOMA system to improve the spectrum efficiency of the system, and adopts full-duplex relay to improve the signal-to-noise ratio of the decoded signal, thereby overcoming the problem of poor communication quality of far-end users in the prior art, and adopts maximum ratio combining technology for near-end users, so that the communication quality of near-end and far-end users in the present invention is improved, and the total achievable rate and spectrum efficiency of the system are improved.

[0027] The present invention can be used in the CR-NOMA communication system of direct transmission and full-duplex relay of future wireless mobile communications. Under the condition of meeting the system interruption probability threshold and fairness, the total achievable rate and spectrum efficiency of the system can be improved, and the communication quality of near-end and far-end users can be improved at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0029] Figure 1 A flow chart of a method for optimizing the performance of a CR-NOMA communication system based on a multi-user scenario provided in an embodiment of the present invention.

[0030] Figure 2 A schematic diagram of a CR-NOMA communication scenario based on a multi-user scenario provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0032] Among them, the drawings are only used for illustrative explanations, showing only schematic diagrams rather than actual drawings, and should not be understood as limitations of the present invention; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0033] The application principle of the present invention is described in detail below in conjunction with the accompanying drawings.

[0034] like Figure 1 As shown, the CR-NOMA communication system performance optimization method based on a multi-user scenario provided by the present invention includes the following steps:

[0035] S201: In time slot t1, SS sends a superimposed signal X(t1) to the full-duplex relay R and the first secondary user D0;

[0036] S202: R decodes the received signal of time slot t1 to obtain D0, D1, ..., D M The desired signal is re-encoded as x0(t1), x1(t1), x2(t1), ...., x M At time slots (t1) and t2, SS sends the superposition code X(t2) to R and D1, and R sends the coded signal to R and secondary users D0, D1, ..., D M ;

[0037] S203: D0 performs maximum ratio combining on the received signal and decodes the signal y0(t2), D m (m∈{1, 2, ..., M}) decodes the received signal y m (t2);

[0038] S204: Calculate D0 and D according to Shannon's formula m The achievable rate of (m∈{1, 2, …, M}) and the user interruption probability are calculated based on the interruption probability definition;

[0039] S205: Maximizing the total achievable rate of the system based on optimal power allocation to the near-end user.

[0040] The application principle of the present invention is further described below in conjunction with the accompanying drawings.

[0041] The CR-NOMA communication system performance optimization method based on a multi-user scenario provided by the embodiment of the present invention is Figure 2 This is achieved in the scenario of Figure 2 In the system, there is a secondary source (SS), multiple primary transmitters (PTs), a primary destination user (PD), a full-duplex relay (R), M+1 secondary users D0, D1, ..., D MAssume SS, D0, D1, ..., D M All are single antennas, R is a dual antenna (one for receiving signals and one for sending signals). SP and h RP Represent the channel coefficients between SS and R and PD respectively. represents SS, R, D0, D1, ..., D M The channel coefficient between Different channel coefficients are independent and identically distributed, and are modeled as zero-mean circularly symmetric complex Gaussian random variables. Assume that all receivers are subject to a zero-mean and variance σ 2 The interference of the primary network (PN) to the secondary network (SN) users is represented by I PS Indicates that its mean is 0 and its variance is τσ 2 , where τ∈(0,1). It is assumed that secondary communication is allowed only when the PD is not interfered by the SN. Therefore, the interference temperature constraint (ITC) of SS and R is T ITC .

[0042] The CR-NOMA communication system performance optimization method based on a multi-user scenario provided by the present invention specifically includes the following steps:

[0043] S201: In time slot t1, SS sends a superimposed signal X(t1).

[0044] In the t1th time slot, the superimposed signal of SS is

[0045]

[0046] where x m (t1) and x0(t1) are D m (m∈{1, 2, …, M}) and the desired signal of D0, and E(|x0(t1)| 2 )=E(|x m (t1)| 2 )=1;α0 and α m D0 and D m The power distribution coefficient satisfies α0<α1<…<α M ;P SS Indicates the transmit power of the SS.

[0047] S202: R decodes the received signal of time slot t1 to obtain D0, D1, ..., D M The desired signal is re-encoded as x0(t1), x1(t1), x2(t1), ...., x M At time slots (t1); t2, SS sends the superposition code X(t2) to R and D0, and R sends the coded signal to R and secondary users D0, D1, ..., D M .

[0048] At time slot t1, the received signal of relay R is

[0049] y R (t1) = g SR X M+1 (t1)+I PS +n R (t1)

[0050] in is the channel coefficient between SS and R, I PS Indicates the interference of PN to SN, n R (t1) is the AWGN on R.

[0051] At time slot t2, the received signal of R is

[0052]

[0053] in represents the self-interference channel coefficient of R, P R represents the transmission power of R, β k Yes D k The power allocation coefficient of (k∈{0, 1, 2, …, M}) satisfies β0<β1<…<β M , n R (t2) is the AWGN on R.

[0054] R decode x m Signal-to-noise ratio (t1)

[0055]

[0056] in is the transmit signal-to-noise ratio of SS, is the transmit signal-to-noise ratio of R.

[0057] S203: D0, D1, ..., D M Decode the received signal.

[0058] The received signal at time slot D0 is

[0059] y0(t1)=g S0 X M+1 (t1)+I PS +n0(t1)

[0060] in is the channel coefficient between SS and D0, n0(t1) is the AWGN on D0, and for simplicity, it is assumed that all secondary receiving nodes are subject to interference from PN I PS .

[0061] According to the NOMA technology decoding principle, D0 needs to use SIC technology to decode D M , D M-1 , ..., D1's expected signal, and then eliminates it in turn, and finally decodes its own expected signal. Therefore, D0 can use the side information x obtained in the SIC process m (t2) Eliminate the interference information in y0(t2) But we consider a more realistic situation, that is, the interference cancellation is not ideal and there is residual interference. So the received signal of time slot D0 at time slot t2 is

[0062]

[0063] in represents the self-interference channel coefficient between R and D0, where x m (t2) and x0(t2) are D m (m∈{1, 2, …, M}) and the desired signal of D0, and E(|x0(t2)| 2 )=E(|x m (t2)| 2 )=1, n0(t2) is the AWGN on D0.

[0064] At time slot t2, the signal-to-noise ratios of D0 decoding its desired signals x0(t1) and x0(t2) from the superimposed signals sent by SS and R can be expressed as

[0065]

[0066] The maximum ratio combining is adopted at D0, so the total signal-to-noise ratio at D0 can be expressed as

[0067]

[0068] D0 decoding signal x m (t2) signal and interference plus noise

[0069]

[0070] t2 time slot D m The received signal at

[0071]

[0072] in It is R and D m The channel coefficient between m (t2) is D m AWGN on.

[0073] D i (1≤i≤m≤M) decode x m The signal-to-noise ratio of (t2) is

[0074]

[0075] S204: Calculate the achievable rates of D1 and D2 according to the Shannon formula, and calculate the user interruption probability based on the interruption probability definition.

[0076] According to Shannon's formula, the expression of the user's achievable rate is derived. m The achievable rates are

[0077]

[0078] and

[0079]

[0080] When the actual achievable data rate during transmission is lower than the target rate, the transmission is interrupted. The interruption probability is an important performance indicator for measuring delay-sensitive transmission. Here, we assume that r0 and r m D0 and D are preset according to the service quality m The achievable rate threshold, and for the convenience of calculation, define

[0081] The D0 decoding signal is divided into two cases. The first case is R decoding D j The expected signal of (j∈{1,…,M}) fails; the second case is that R successfully decodes D j (j∈{1,…,M}), D2 fails to decode its own expected signal x0(t2).

[0082] The interruption probability of D0 is

[0083]

[0084] in

[0085] D mThe decoding signal is divided into two cases. The first case is R decoding D j The expected signal of (j∈{m+1,…,M}) fails; the second case is that R successfully decodes D j (j∈{m+1,…,M}), D2 decodes its own expected signal x m (t2) Failure.

[0086] when and When D m The OP is

[0087]

[0088] when or When D m The OP is

[0089]

[0090] S205: Satisfy system fairness and user interruption probability thresholds and maximize the total achievable rate of the system.

[0091] Maximizing the total achievable rate of the system, according to the characteristics of the CR-NOMA communication system in a multi-user scenario, and satisfying the user interruption probability threshold, the optimization objective function and constraints of the system can be obtained as follows:

[0092]

[0093] F=F *

[0094]

[0095] Where C0 and C m Represent D0 and D m The achievable rate, k0 represents the interruption probability threshold of the D0 system, and Represent D0 and D m The interruption probability, Represents the system fairness factor.

[0096] The basic idea of ​​this method is as follows: Since D0 is a user in the cell center, less power resources are allocated. Assume that the power allocation scheme of SS sending superimposed signals in time slots t1 and t2 is the same. If α M =x, then x≥0.5. Let α M According to the determined step size, the value is incremented in [0.5, 1), and according to the channel condition information, α0<α1<…<α M , We can get αm-1 The corresponding search interval is We can get D m All power allocation (n,M) matrices P that meet the conditions A Finally, the search interval corresponding to α0 is The search interval of α0 is further calculated by the OP threshold and the achievable rate threshold. The intersection of the two is taken to obtain the search interval of α0 [a, b]. Similarly, D at R can be obtained. m All power allocation (n,M) matrices P that meet the conditions B and β0's search interval [c, d], and then find the system fairness index factor F according to the binary search method * The optimal transmission allocation scheme for the system under the circumstances is finally found by using the sorting algorithm to find the power allocation scheme that can maximize the total rate of the system.

[0097] The method flow is as follows

[0098]

[0099] An embodiment of the present application also provides a computer-readable storage medium, which may include a computer program or instructions. When the computer program or instructions are executed on a computer, the computer executes the CR-NOMA communication system performance optimization method described in the above embodiment.

[0100] An embodiment of the present application provides a computer program product, including a computer program or instructions. When the computer program or instructions are executed on a computer, the computer executes the CR-NOMA communication system performance optimization method described in the above embodiment.

[0101] The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using a software program, the above embodiments may appear in whole or in part in the form of a computer program product, which includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part.

[0102] It should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0103] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A CR-NOMA communication system performance optimization method based on a multi-user scenario, characterized in that: The method specifically comprises the following steps: S201: t1 time slot, secondary source SS sends superimposed signal To the full-duplex relay R and the first secondary user D0; where x m (t1) and x0(t1) are D m (m∈{1, 2, ..., M}) and the desired signal of D0, and E(|x0(t1)| 2 )=E(|x m (t1)| 2 )=1;α0 and α m D0 and D m The power distribution coefficient satisfies P SS Indicates the transmission power of SS; S202: R decodes the received signal of time slot t1 to obtain D0, D1, ..., D M The desired signal is re-encoded as x0(t1), x1(t1), x2(t1), ...., x M At time slots (t1) and t2, SS sends the superposition code X(t2) to R and D1, and R sends the coded signal to R and secondary users D0, D1, ..., D M ; S203: D0 performs maximum ratio combining on the received signal and decodes the signal y0(t2), D m (m∈{1, 2, ..., M}) decodes the received signal y m (t2); S204: Calculate D0 and D according to Shannon's formula m (m∈{1, 2, ..., M}) and calculate the user interruption probability based on the interruption probability definition, where D0, D1, ..., D M The interruption probability is or When D0, D1, ..., D M The interruption probability is equal to 1, where β m Yes D m The power allocation factor, R m Indicates D m The target rate; S205: Based on the optimal power allocation of near-end users, the total achievable rate of the system is maximized. According to the characteristics of the CR-NOMA communication system in a multi-user scenario, the user interruption probability threshold is met. The optimization objective function and constraints of the system can be obtained as follows: Where C0 and C m Represent D0 and D m The achievable rate, k0 represents the interruption probability threshold of the D0 system, and Represent D0 and D m The interruption probability, represents the system fairness factor, The time slots D0 and D2 are t2 respectively. m The achievable rates, r0 and r m D0 and D are preset according to the service quality m The achievable rate threshold.

2. A CR-NOMA communication system performance optimization method based on a multi-user scenario as claimed in claim 1, characterized in that: The R transmission mode of S202 is that R re-encodes the decoded signal according to the power allocation factor, and sends the encoded signal to R, and D0, D1, ..., D M .

3. A CR-NOMA communication system performance optimization method based on a multi-user scenario as claimed in claim 1, characterized in that: The non-ideal elimination of the self-interference signal by R in S202 and D0 in S203 will be affected by the residual interference.

4. A CR-NOMA communication system performance optimization method based on a multi-user scenario as claimed in claim 1, characterized in that: The interruption probability in S204 is the probability that the actual achievable data rate is lower than the target rate during the transmission process.

5. A CR-NOMA communication system performance optimization method based on a multi-user scenario as claimed in claim 1, characterized in that: The maximization of the total achievable rate of the system in S205 is performed while ensuring user fairness, thereby maximizing the total achievable rate of the system.

6. A CR-NOMA communication system performance optimization method based on a multi-user scenario as claimed in claim 5, characterized in that: The total achievable rate of the system is a piecewise function and the objective function contains multivariable factors.

7. An electronic device, characterized in that: include: A processor and a memory, wherein the memory is coupled to the processor, the memory is used to store computer program code, and the computer program code includes computer instructions. When the processor reads the computer instructions from the memory, the electronic device executes the CR-NOMA communication system performance optimization method based on a multi-user scenario as described in any one of claims 1 to 6.

8. A computer storage medium, characterized in that It includes computer instructions. When the computer instructions are executed on a terminal, the terminal executes the CR-NOMA communication system performance optimization method based on a multi-user scenario as described in any one of claims 1 to 6.

9. A computer program product, characterized in that When the computer program product is run on a computer, the computer is enabled to execute the CR-NOMA communication system performance optimization method based on a multi-user scenario as described in any one of claims 1 to 6.

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