An uplink cell-free massive MIMO system with zf and d2d

Abstract

The application relates to an uplink non-cell massive MIMO system adopting ZF and D2D, which comprises a central processing unit (CPU), an access point (AP), a cell-free user equipment (CFUE) and a device-to-device user equipment (DUE); an analysis method of the system comprises: calculating a closed-form expression of the CFUE rate under the system architecture; calculating a closed-form expression of the DUE rate under the system architecture; and obtaining the sum rate of the system. The application has the beneficial effect that the application can explain how some important parameters, such as the number of AP / CFUEs, the number of antennas of each AP / CFUE and the density of DUEs, affect the system performance, and highlights the significance of cooperation between the cell-free massive MIMO and the D2D communication.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and more specifically, to an uplink non-cellular massive MIMO system employing ZF and D2D. Background Technology

[0002] Currently, the explosive growth of high-definition mobile multimedia, the abundance of data-hungry applications running on it, and the significant increase in demand for fast mobile internet services have led to a growing need to support the data traffic and high transmission rates of the upcoming sixth-generation (6G) communications, which cannot be adequately supported by traditional cellular network architectures. Furthermore, insufficient air interface spectrum and unprecedented traffic surges on backhaul links are another significant factor limiting the performance of wireless systems, making them unsuitable for latency-sensitive tasks. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide an uplink non-cellular massive MIMO system using ZF and D2D.

[0004] In the first aspect, an uplink non-cellular massive MIMO system using ZF and D2D is provided, including: a central processing unit (CPU), an access point (AP), non-cellular user CFUE, and device-to-device user DUE.

[0005] Each AP and CFUE is equipped with N antennas and one antenna respectively; each DUE is equipped with N D One antenna.

[0006] Secondly, an analysis method for uplink cellless massive MIMO systems employing ZF and D2D as described in the first aspect is provided, including:

[0007] S1. Establish an uplink non-cellular massive MIMO system architecture using ZF and D2D;

[0008] S2. Calculate the closed-form expression for the CFUE rate under the system architecture;

[0009] S3. Calculate the closed-form expression for the DUE rate under the system architecture;

[0010] S4, obtain the system's sum and rate.

[0011] Preferably, S1 includes:

[0012] S101. Establish an uplink cellular-free massive MIMO system architecture including M APs, K CFUEs, and J pairs of DUEs, using g mk The channel vector from k CFUEs to m APs is represented as:

[0013]

[0014] Where, β mk The vector h represents the large-scale fading coefficients between the k-th CFUE and the m-th AP. mk This represents the small-scale fading vector, whose entries are assumed to be independent and identically distributed cyclic symmetric complex Gaussian random variables;

[0015] In the j-th pair of DUEs, the channel coefficient from the DUE transmitter to the DUE receiver is expressed as:

[0016]

[0017] Where, β jj′ h represents the large-scale fading coefficient. jj′ The entries corresponding to the small-scale fading vector are assumed to be (0,1);

[0018] S102. Perform channel estimation. The pilot signals received at the m-th AP and the j-th DUE receiver are represented as follows:

[0019]

[0020]

[0021] Where, ρ cf and ρ d t represents the maximum transmit power of the CFUE and DUE links respectively. k and s j This indicates the pilot signals assigned to CFUE and DUE; additionally, W m and W j These represent additive white Gaussian noise;

[0022] S103. Use the minimum mean square error method to obtain the estimated channel and its covariance;

[0023] S104. Analyze the uplink data link data of the system.

[0024] Preferably, in S102, by... and Projected to t k and s j The processed signal is represented as follows:

[0025]

[0026]

[0027] in, Used to eliminate coupling, and ||t k || 2 =1.

[0028] Preferably, in S103, the AP to CFUE channel g mk Estimated channel The calculation is as follows:

[0029]

[0030] in, This indicates the desired operation; for the j-th pair of DUE transmitter to DUE receiver g jj Estimated channel Represented as:

[0031]

[0032] and covariance η mk and η jj Represented as:

[0033]

[0034]

[0035] and The following relationship exists:

[0036]

[0037] Where, ε mk and ε jj They represent g respectively mk and g jj estimation error; estimation channel and estimation error ε mk ε jj The statistical properties are expressed as follows:

[0038]

[0039]

[0040] Among them, I N This represents a square matrix of dimension N. Indicates a dimension of N D A square formation.

[0041] As a preferred option, in S104, for ease of analysis, t is used. k This further represents the data signal sent by the k-th CFUE, s jThis can be further represented as the data signal transmitted by the j-th DUE transmitter, and respectively satisfying The received signals of the CPU and the j-th DUE receiver are represented as follows:

[0042]

[0043]

[0044] in, n u =[n 1u ,…,n Mu ] T Indicates additive noise. t = [t1, t2, ..., t K ];s=[s1,s2,…,s J ];

[0045] By using a linear detector to separate the received signal, the processed signal is represented as follows:

[0046]

[0047] in, p k g is a column of matrix P. l =[g 1l ,g 2l ,…,g Ml ];t l =[t 1l ,t 2l ,…,t Ml ].

[0048] After performing the appropriate signal processing, the signal received by the k-th CFUE is represented as follows:

[0049]

[0050] Where, ε l =[ε 1l ,ε 2l ,…,ε Ml ].

[0051] Preferably, in S2, the lower bound of the achievable rate of the k-th CFUE is expressed as:

[0052]

[0053] Wherein, Ψ is represented as:

[0054]

[0055]

[0056] Preferably, in S2, by using an MRC receiver, the received signal of the j-th DUE receiver is represented as:

[0057]

[0058] in, and

[0059] Therefore, the signal received by the j-th DUE receiver is represented as:

[0060]

[0061] Preferably, in S3, by using and The traversal rate achievable by the j-th DUE receiver is:

[0062]

[0063] Thirdly, a computer storage medium is provided, wherein a computer program is stored therein; when the computer program is run on a computer, the computer performs the analysis method for uplink non-cellular massive MIMO systems using ZF and D2D as described in any of the second aspects.

[0064] The beneficial effects of this invention are as follows: This invention discloses an uplink cellular-free massive MIMO system using ZF and D2D, and performs rate analysis. The derivation of the achievable total uplink rate serves as a tool to explain how some important parameters, such as the number of APs / CFUEs, each AP / CFUE / antenna, and the density of DUEs, affect system performance, highlighting the significance of cooperation between cellular-free massive MIMO and D2D communication. Attached Figure Description

[0065] Figure 1 A flowchart illustrating an analysis method for an uplink non-cellular massive MIMO system employing ZF and D2D techniques;

[0066] Figure 2 This is a schematic diagram of the achievable total uplink rate. Detailed Implementation

[0067] The present invention will be further described below with reference to embodiments. The description of the embodiments below is only for the purpose of helping to understand the present invention. It should be noted that those skilled in the art can make several modifications to the present invention without departing from the principle of the present invention, and these improvements and modifications also fall within the protection scope of the claims of the present invention.

[0068] This invention discloses a transmission architecture for a zero-force (ZF) receiver for device-to-device (D2D) communication in a cellless massive MIMO system, followed by a rate analysis. It is assumed that D2D users (DUEs) can utilize orthogonal radio resources to improve the efficiency of scarce resource utilization, or reuse time-frequency spectrum resources currently used by cellless users (CFUEs). It is also assumed that imperfect channel state information (CSI) is achievable. Then, closed-form representations of CFUEs and DUEs are obtained using usage and forgetting constraints, providing a lower bound on the approximate achievable rate of the two communication links. First, the minimum mean square error (MMSE) estimate for all channels is calculated. Then, the derivation of the achievable total uplink rate provides a tool to explain how important parameters, such as the number of APs / CFUEs, each AP / CFUE / antenna, and the density of DUEs, affect system performance, highlighting the significance of cooperation between cellless massive MIMO and D2D communication.

[0069] Specifically, as one embodiment, this application provides an analysis method for an uplink cellular-free massive MIMO system employing ZF and D2D, including:

[0070] S1. Establish an uplink non-cellular massive MIMO system architecture using ZF and D2D;

[0071] S2. Calculate the closed-form expression for the CFUE rate under the system architecture;

[0072] S3. Calculate the closed-form expression for the DUE rate under the system architecture;

[0073] S4, obtain the system's sum and rate.

[0074] S1 includes:

[0075] S101. Establish an uplink cellular-free massive MIMO system architecture comprising M APs, K CFUEs, and J pairs of DUEs, wherein each AP and CFUE is equipped with N antennas and one antenna, respectively. Furthermore, each DUE has N antennas. D Antenna. Using g mk The channel vector from k CFUEs to m APs is represented as:

[0076]

[0077] Where, β mk The vector h represents the large-scale fading coefficients between the k-th CFUE and the m-th AP. mk This represents the small-scale fading vector, whose entries are assumed to be independent and identically distributed cyclic symmetric complex Gaussian random variables;

[0078] In the j-th pair of DUEs, the channel coefficient from the DUE transmitter to the DUE receiver is expressed as:

[0079]

[0080] Where, β jj′ h represents the large-scale fading coefficient. jj′ The entries corresponding to the small-scale fading vector are assumed to be (0,1);

[0081] S102. Before signal transmission, channel estimation is usually required. The pilot signals received at the m-th AP and the j-th DUE receiver are represented as follows:

[0082]

[0083]

[0084] Where, ρ cf and ρ d t represents the maximum transmit power of the CFUE and DUE links respectively. k and s j This indicates the pilot signals assigned to CFUE and DUE; additionally, W m and W j These represent additive white Gaussian noise;

[0085] S103. Use the minimum mean square error (MMSE) method to obtain the estimated channel and its covariance;

[0086] S104. Analyze the uplink data link data of the system.

[0087] In S102, by... and Projected to t k and s j The processed signal is represented as follows:

[0088]

[0089]

[0090] in, Used to eliminate coupling, and ||t k || 2 =1.

[0091] In S103, the AP to CFUE channel g mk Estimated channel The calculation is as follows:

[0092]

[0093] in, This indicates the desired operation;

[0094] For the k-th pair of DUE transmitter to DUE receiver g jj Estimated channel Represented as:

[0095]

[0096] and covariance η mk and η jj Represented as:

[0097]

[0098]

[0099] and The following relationship exists:

[0100]

[0101] Where, ε mk and ε jj They represent g respectively mk and g jj estimation error; estimation channel and estimation error ε mk ε jj The statistical properties are expressed as follows:

[0102]

[0103]

[0104] Among them, I N This represents a square matrix of dimension N. Indicates a dimension of N D A square formation.

[0105] In S104, t is used. k s represents the data signal sent by the k-th CFUE. j Let j be the data signal transmitted by the j-th DUE transmitter, and satisfy the following conditions respectively. The received signals of the CPU and the j-th DUE receiver are represented as follows:

[0106]

[0107]

[0108] in, n u =[n 1u ,…,n Mu ] T Indicates additive noise. t = [t1, t2, ..., t k ];s=[s1,s2,…,s J ];

[0109] By using a linear detector to separate the received signal, the processed signal is represented as follows:

[0110]

[0111] in, p k g are columns of matrix P; l =[g 1l ,g 2l ,…,g Ml ];t l =[t 1l ,t 2l ,…,t Ml ].

[0112] After performing the appropriate signal processing, the signal received by the k-th CFUE is represented as follows:

[0113]

[0114] Where, ε l =[ε 1l ,ε 2l ,…,ε Ml ].

[0115] In S2, the lower bound of the achievable rate of the k-th CFUE is expressed as:

[0116]

[0117] Where ψ is represented as:

[0118]

[0119]

[0120] In S2, using an MRC receiver, the received signal of the j-th DUE receiver is represented as:

[0121]

[0122] in, and

[0123] Therefore, the signal received by the j-th DUE receiver is represented as:

[0124]

[0125] In S3, by using and The traversal rate achievable by the j-th DUE receiver is:

[0126]

[0127] Based on the above simple expressions, the sum and rate of the system can be obtained.

Claims

1. An analysis method for uplink cellular-free massive MIMO systems employing ZF and D2D, characterized in that, include: S1. Establish an uplink non-cellular massive MIMO system architecture using ZF and D2D; the system includes: a central processing unit (CPU), access points (APs), non-cellular user CFUEs, and device-to-device user DUEs; Each AP and CFUE is equipped with One antenna and one antenna; each DUE is equipped with One antenna; S1 includes: S101, Establish including One app, CFUE and For the uplink cellular-free massive MIMO system architecture of DUE, using Indicates from CFUE to The channel vectors of each AP are represented as: ； in, Indicates the first The first CFUE to the first Large-scale fading coefficients between APs, vector This represents the small-scale fading vector, whose entries are assumed to be independent and identically distributed cyclic symmetric complex Gaussian random variables; In the j-th pair of DUEs, the channel coefficient from the DUE transmitter to the DUE receiver is expressed as: ； in, Represents the large-scale fading coefficient. Corresponding to the small-scale fading vector, its entries are assumed to be: ; S102, Perform channel estimation, in the... The AP and the first The pilot signals received at each DUE receiver are represented as follows: ； ； in, and These represent the maximum transmit power of the CFUE and DUE links, respectively. and This indicates the pilot signals allocated to CFUE and DUE; in addition, and These represent additive white Gaussian noise; S103. Use the minimum mean square error method to obtain the estimated channel and its covariance; S104. Analyze the uplink data link data of the system; In S104, using Indicates the first Data signals sent by each CFUE For the first The data signals transmitted by each DUE transmitter satisfy the following conditions: , Then the CPU and the first The received signals of each DUE receiver are represented as follows: ； ； in, , , Indicates additive noise. , ; ; ; By using a linear detector to separate the received signal, the processed signal is represented as follows: ； in, , , It is a matrix The column; ; ; By performing appropriate signal processing, the first... The signals received by each CFUE are represented as follows: ； in, ; S2. Calculate the closed-form expression for the CFUE rate under the system architecture; S3. Calculate the closed-form expression for the DUE rate under the system architecture; S4, obtain the system's sum and rate.

2. The analysis method for uplink cellular-free massive MIMO systems using ZF and D2D as described in claim 1, characterized in that, In S102, by... and Projected to and The processed signal is represented as follows: ； ； in, Used to eliminate coupling, and .

3. The analysis method for uplink cellular-free massive MIMO systems using ZF and D2D as described in claim 2, characterized in that, In S103, the AP to CFUE channel Estimated channel The calculation is as follows: ； in, This indicates the desired operation; For the DUE transmitter to DUE receiver Estimated channel Represented as: ； and covariance and Represented as: ； ； and The following relationship exists: ； in, and They represent and estimation error; estimation channel , and estimation error , The statistical properties are expressed as follows: ； ； in, , .

4. The analysis method for uplink cellular-free massive MIMO systems using ZF and D2D as described in claim 3, characterized in that, In S2, the first The lower bound of the achievable rate for a CFUE is expressed as: ； in, Represented as: ； 。 5. The analysis method for uplink cellless massive MIMO systems using ZF and D2D as described in claim 4, characterized in that, In S2, by using an MRC receiver, in the... The received signal of each DUE receiver is represented as: ； in, , , and ; Therefore, the first The signal received by the DUE receiver is represented as follows: ； 。 6. The analysis method for uplink cellular-free massive MIMO systems using ZF and D2D as described in claim 5, characterized in that, In S3, by using and , No. The traversal rate achievable by a number of DUE receivers is: 。 7. A computer storage medium, characterized in that, The computer storage medium stores a computer program; when the computer program is run on the computer, it causes the computer to execute the analysis method for uplink non-cellular massive MIMO systems using ZF and D2D as described in any one of claims 1 to 6.

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