WO2024113524A1 - Procédé et module de détermination d'efficacité spectrale de système urllc nafd - Google Patents

Procédé et module de détermination d'efficacité spectrale de système urllc nafd Download PDF

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WO2024113524A1
WO2024113524A1 PCT/CN2023/079495 CN2023079495W WO2024113524A1 WO 2024113524 A1 WO2024113524 A1 WO 2024113524A1 CN 2023079495 W CN2023079495 W CN 2023079495W WO 2024113524 A1 WO2024113524 A1 WO 2024113524A1
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uplink
downlink
user
spectrum efficiency
users
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PCT/CN2023/079495
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English (en)
Chinese (zh)
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夏心江
王东明
李笑寒
孙文菲
卜颖澜
尤肖虎
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网络通信与安全紫金山实验室
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Publication of WO2024113524A1 publication Critical patent/WO2024113524A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0452—Multi-user MIMO systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Definitions

  • the present application relates to the field of wireless communication transmission technology, and in particular to a method, device, electronic device and readable storage medium for determining the spectrum efficiency of a cellular-free massive MIMO uRLLC system based on NAFD.
  • CCFD Co-frequency Co-time Full Duplex
  • CLI Cross-Link Interference
  • NAFD Network-Assisted Full Duplex
  • HD Hybrid duplex Communication
  • the cell-free massive MIMO Multiple-Input and Multiple-Output
  • a MIMO network with a distributed antenna system, where each Aps (Access Point) covers a wide area to coherently serve a large number of users on the same video resource and is connected to the central processing unit (CPU) through a backhaul link.
  • NAFD combined with cell-free massive MIMO is expected to overcome inter-cell interference and provide uniform QoS (Quality of Service) without handoff to cell-edge users, thereby enabling the uRLLC (Ultra-reliable and Low Latency Communications) transmission scheme in the system.
  • QoS Quality of Service
  • the performance of the existing NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system cannot meet user needs, and the relevant technologies are all aimed at improving the receiver of uRLLC in non-cellular massive MIMO combined with CCFD, including uplink and downlink precoding, reliability and delay balance, etc. It is understandable that CCFD and NAFD are not the same, and the relevant methods of the receiver of uRLLC in non-cellular massive MIMO combined with CCFD cannot be fully applied to the joint transceiver of uRLLC in non-cellular massive MIMO based on NAFD.
  • the present application provides a method, device, electronic device and readable storage medium for determining the spectrum efficiency of a NAFD-based non-cellular massive MIMO uRLLC system, which effectively improves the performance of the NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system to meet users' high performance requirements for the NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system.
  • the embodiments of the present invention provide the following technical solutions:
  • An embodiment of the present invention provides a method for determining the spectrum efficiency of a cellular-free massive MIMO uRLLC system based on NAFD, including:
  • the uplink spectrum efficiency is determined on the basis of ensuring the maximum decoding error probability of uplink and downlink users;
  • the uplink and downlink transceivers are jointly optimized to determine the target spectrum efficiency by maximizing the uplink and downlink weighted and spectrum efficiency.
  • Another aspect of the present invention provides a spectral efficiency determination device for a cellular-free massive MIMO uRLLC system based on NAFD, including:
  • the spectrum efficiency determination module is used to determine the inter-user interference channel of uplink and downlink users, the channel from uplink users to R-APs, the channel from downlink users to T-APs, and the uplink users.
  • the transmission power and system noise are taken into consideration to determine the uplink and downlink spectrum efficiency on the basis of ensuring the maximum decoding error probability of uplink and downlink users; each user works in half-duplex mode;
  • the spectrum efficiency optimization module is used to jointly optimize the uplink and downlink transceivers based on the power consumption constraints and service quality constraints of the uplink and downlink users, and determine the target spectrum efficiency by maximizing the uplink and downlink weighted and spectrum efficiency.
  • An embodiment of the present invention also provides an electronic device, comprising a processor, wherein the processor is used to implement the steps of the method for determining the spectrum efficiency of a NAFD-based non-cellular massive MIMO uRLLC system as described in any of the preceding items when executing a computer program stored in a memory.
  • an embodiment of the present invention further provides a readable storage medium, on which a computer program is stored.
  • the computer program is executed by a processor, the steps of the method for determining the spectrum efficiency of a NAFD-based non-cellular massive MIMO uRLLC system as described in any of the preceding items are implemented.
  • the advantage of the technical solution provided in the present application is that, under the power consumption constraints of uplink and downlink users and the QoS constraints of uplink and downlink users, the uplink and downlink transceivers in the NAFD-based cellless massive MIMO ultra-high reliability and low latency system are optimized to maximize the system weighting and spectrum efficiency, and the performance of the NAFD-based cellless massive MIMO ultra-high reliability and low latency system is effectively improved to meet the high performance requirements of users for the NAFD-based cellless massive MIMO ultra-high reliability and low latency system.
  • the embodiments of the present invention also provide corresponding implementation devices, electronic devices and readable storage media for the spectrum efficiency determination method of the NAFD-based non-cellular massive MIMO uRLLC system, which further makes the method more practical, and the devices, electronic devices and readable storage media have corresponding advantages.
  • FIG1 is a flow chart of a method for determining the spectrum efficiency of a cellular-free massive MIMO uRLLC system based on NAFD provided by an embodiment of the present invention
  • FIG2 is a schematic diagram of a framework of an exemplary application scenario provided by an embodiment of the present invention.
  • FIG3 is a schematic diagram showing performance comparison of different methods in a verification embodiment provided by an embodiment of the present invention.
  • FIG4 is a schematic diagram showing a comparison of spectrum efficiencies corresponding to different methods in a first exemplary verification embodiment provided by an embodiment of the present invention
  • FIG5 is a schematic diagram of the relationship between spectrum efficiency and T-AP power constraint provided by an embodiment of the present invention.
  • FIG6 is a schematic diagram showing a comparison of spectrum efficiencies corresponding to different methods in a second exemplary verification embodiment provided by an embodiment of the present invention.
  • FIG7 is a schematic diagram showing a comparison of spectrum efficiencies corresponding to different methods in a third exemplary verification embodiment provided by an embodiment of the present invention.
  • FIG8 is a schematic diagram of comparing spectrum efficiencies corresponding to different methods in a fourth exemplary verification embodiment provided by an embodiment of the present invention.
  • FIG9 is a structural diagram of a specific implementation of a device for determining spectrum efficiency of a cellular-free massive MIMO uRLLC system based on NAFD provided in an embodiment of the present invention
  • FIG. 10 is a structural diagram of a specific implementation of an electronic device provided in an embodiment of the present invention.
  • FIG 1 is a flow chart of a method for determining the spectrum efficiency of a NAFD-based cellular-free massive MIMO uRLLC system provided in an embodiment of the present invention.
  • the NAFD-based cellular-free massive MIMO uRLLC system applicable to this embodiment is shown in Figure 2.
  • the NAFD-based cellular-free massive MIMO uRLLC system includes multiple APs, which are connected to the central processing unit (CPU) through a backhaul link.
  • Each AP can freely choose to work in CCFD, HD or other flexible duplex modes.
  • the receiving AP can be called R-AP
  • the sending AP can be called T-AP.
  • Each user in the uplink and downlink works in half-duplex mode.
  • the NAFD-based cellular-free massive MIMO uRLLC system may include L T-APSs, Z R-APSs, K downlink users, and J uplink users.
  • Each T-AP and R-AP may include M antennas, and each user has a single antenna.
  • the index set of T-APs can be expressed as The index set of R-AP can be expressed as The index set of downlink users can be expressed as The index set of uplink users can be expressed as The CPU processes the downlink signal and transmits it to the T-APs, which then transmit the received downlink signal to the downlink user.
  • the R-APs receive the signal from the uplink user and forward it to the CPU for further processing.
  • the downlink channel h D,k between the T-APs and the downlink user k can be expressed as represents the transpose of the downlink channel between the Lth T-AP and the kth downlink user
  • the uplink channel h U,j between the jth uplink user and R-APs can be expressed as represents the transposition of the uplink channel from the jth uplink user to the zth R-AP
  • the interference (IAI) between T-APs and the zth R-AP The channel can be This can be modeled as:
  • ⁇ D,k represents the large-scale fading from T-APs to the k-th downlink user
  • g D,k represents the small-scale fading from T-APs to the k-th downlink user
  • ⁇ IAI,j,k represents the large-scale fading from the j-th uplink user to the k-th downlink user
  • g IAI,j,k represents the small-scale fading from the j-th uplink user to the k-th downlink user
  • ⁇ U,j represents the large-scale fading from the j-th uplink user to R-APs
  • g U,j represents the small-scale fading from the j-th uplink user to R-APs
  • ⁇ IAI,z represents the large-scale fading from T-APs to the z-th R-AP
  • G IAI,z represents the small-scale fading from T-APs to the z-th R-AP.
  • ⁇ D,L,k represents the large-scale fading from the Lth T-AP to the kth downlink user
  • ⁇ U,j,Z represents the large-scale fading from the jth uplink user to the Zth R-AP
  • ⁇ IAI,L,z represents the large-scale fading from the Lth T-AP to the zth R-AP
  • I M represents the identity matrix of dimension M.
  • the channel vector from the lth T-AP to the kth downlink user represents the channel vector from the jth uplink user to the zth R-AP.
  • ⁇ is the first parameter
  • ⁇ IAI,U,D ⁇ is the second parameter
  • ⁇ IAI,U,D ⁇ is the third parameter
  • the following discusses the optimization design method of the uRLLC uplink and downlink receiver precoding vector and uplink user transmission power under the QoS constraints and power consumption constraints of the uplink and downlink of the NAFD-based non-cellular massive MIMO uRLLC system provided by this embodiment, which can maximize the weighted sum spectrum efficiency of the NAFD-based non-cellular massive MIMO uRLLC system and obtain the target spectrum efficiency of the uplink and downlink users.
  • the implementation process may include the following contents:
  • S101 Determine the uplink and downlink spectrum efficiencies based on the maximum decoding error probability of the uplink and downlink users, according to the inter-user interference channels of the uplink and downlink users, the channels from the uplink users to the R-APs, the channels from the downlink users to the T-APs, the transmission power of the uplink users, and the system noise.
  • the uplink and downlink transceivers are jointly optimized with the goal of maximizing the uplink and downlink weighted and spectrum efficiencies to determine the target spectrum efficiency.
  • the inter-user interference channel refers to the inter-user interference channel between the uplink user and the downlink user
  • the user data signal refers to the data signal of the uplink user and the data signal of the downlink user
  • the channel from the downlink user to T-APs refers to the channel from the downlink user to each T-AP
  • the uRLLC uplink and downlink spectrum efficiency includes the downlink spectrum efficiency and the uplink spectrum efficiency.
  • the uplink and downlink transceivers are jointly optimized to obtain the transceiver of the system, and the target spectrum efficiency of the current system is determined.
  • the transceiver mentioned in the present application includes transmitters at the user and the T-AP, and a receiver at the R-AP.
  • the transmitter at the user corresponds to p U,j
  • the transmitter at the T-AP corresponds to w D,k
  • the receiver at the R-AP corresponds to u U,j .
  • the uplink and downlink transceivers in the NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system are optimized to maximize the system weighting and spectrum efficiency, and the uplink and downlink user weighting and spectrum efficiency can be maximized under the condition of limited code length, effectively improving the performance of the NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system, so as to meet the user's high performance requirements for the NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system.
  • step S101 there is no limitation on how to perform step S101.
  • an optional method for determining the spectrum efficiency of uplink and downlink is provided, which includes the following steps:
  • LBR long block regime
  • the uplink spectrum efficiency is determined on the basis of ensuring the maximum decoding error probability of the uplink user.
  • the user received signal at the downlink user is referred to as the user received signal
  • the received signal at the R-AP is referred to as the AP received signal.
  • the received signal can be directly obtained, and the corresponding signal data, interference data, noise data and channel data are obtained by parsing the received signal, and then the maximum uplink and downlink spectrum efficiency is calculated using these data.
  • the obtained user received signal relationship can be expressed as:
  • y D,k is the user received signal at the kth downlink user
  • D represents the downlink channel
  • U represents the uplink channel
  • h D,k is the downlink channel of T-APs and the k-th downlink user
  • k' is the k'th downlink user
  • w D,k is the precoding vector of the k'th downlink user
  • w D,k' is the precoding vector of the k'th downlink user
  • s D,k is the data signal of the k'th downlink user
  • s D,k' is the data signal of the k'th downlink user
  • h IUI,j,k is the inter-user interference channel between the k'th downlink user and the j'th uplink user
  • s U,j is the data signal of the j'th uplink user
  • p U,j is the transmission power of the j'th uplink user
  • n D,k is the additive white Gaussian noise AWGN at the k'th downlink user receiver, with zero mean and variance of
  • the SINR signal calculation relationship can be expressed as:
  • the achievable downlink spectrum efficiency under long code can be further calculated based on the Shannon rate function.
  • the achievable downlink spectrum efficiency can be expressed as:
  • the downlink spectrum efficiency calculation formula can be used to calculate the maximum downlink spectrum efficiency; the downlink spectrum efficiency calculation formula can be expressed as:
  • r D,k is the signal to interference plus noise ratio at the kth downlink user
  • w D,k is the precoding vector of the kth downlink user
  • rate RD,k is the downlink spectrum efficiency corresponding to the kth downlink user
  • Q -1 () is the inverse of the Gaussian Q function
  • ⁇ k is the maximum decoding error probability of the kth downlink user
  • N BT
  • N is the given code length
  • B is the transmission bandwidth
  • T is the transmission time slot
  • e is the natural logarithm.
  • the Gaussian Q function can be expressed as
  • the AP receiving signal of the zth R-AP may be expressed as:
  • H IAI,z is the inter-antenna interference channel from the zth R-AP to T-APs
  • h U,j,z is the uplink channel from the jth uplink user to the zth R-AP
  • n U,z is the zero-mean additive white Gaussian noise at the zth R-AP, with a variance of
  • the IAI channel H IAI,l,z is modeled as in represents the non-ideal channel between the lth T-AP and the zth R-AP, represents the corresponding estimated channel of the non-ideal channel between the lth T-AP and the zth R-AP, represents the channel estimation error of the non-ideal channel between the lth T-AP and the zth R-AP, and in, represents the M*M identity matrix, where M is a real number. is the residual error gain at the zth R-AP for the lth T-AP, which is used to
  • the baseband representation relationship can be first called to determine the uplink baseband signal of the zth R-AP; the baseband representation relationship can be expressed as:
  • noise calculation formula in, set up is the combined vector used to demodulate the jth uplink user data signal s U,j at the zth R-AP. Then the noise calculation formula is called to calculate the signal to interference plus noise ratio of the jth uplink user at the CPU; the noise calculation formula can be expressed as:
  • the jth uplink user interference plus noise power ⁇ U,j can be expressed as:
  • the achievable uplink spectrum efficiency of the jth uplink user can be expressed as Similarly, for a given channel code block length N, in order to ensure that the maximum decoding error probability of the jth uplink user does not exceed ⁇ j , the maximum uplink spectrum efficiency can be calculated by calling the uplink spectrum efficiency calculation formula; the uplink spectrum efficiency calculation formula can be expressed as:
  • the uplink baseband signal is the channel estimation error of the non-ideal channel from the zth R-AP to T-APs
  • r U,j is the signal to interference plus noise ratio of the jth uplink user at the CPU
  • ⁇ U,j is the interference plus noise power at the jth uplink user
  • H represents the conjugate transpose
  • R U,j is the uplink spectrum efficiency corresponding to the jth uplink user, is the achievable uplink spectrum efficiency of the jth uplink user
  • ⁇ j is the maximum decoding error probability of the jth uplink user.
  • Q -1 () is the inverse of the Gaussian Q function
  • N is the given code length.
  • the uRLLC system weighted and spectral efficiency is maximized under the transmission power and QoS constraints, and the transceivers ⁇ w D,k ,u U,j ,p U,j ⁇ are jointly optimized. That is, the uplink and downlink transceivers and user transmission power are jointly optimized by calling the uRLLC system optimization relation, and the uRLLC system optimization relation can be expressed as:
  • ⁇ w D,k ,u U,j ,p U,j ⁇ represents the parameters corresponding to the transceiver
  • w D,k is the precoding vector of the k-th downlink user
  • u U,j is the combined vector used to demodulate the data signal of the j-th uplink user
  • D represents the downlink channel
  • U represents the uplink channel
  • ⁇ D,k is the spectrum efficiency weight of the k-th downlink user
  • ⁇ U,j is the spectrum efficiency weight of the j-th uplink user
  • RD,k is the downlink spectrum efficiency corresponding to the k-th downlink user
  • RU ,j is the uplink spectrum efficiency corresponding to the j-th uplink user
  • w D,l,k is the precoding vector of the k-th downlink user in the l-th T-AP
  • PD downlink spectrum efficiency corresponding to the j-th uplink user
  • the present application also provides two different methods to solve the problem of uRLLC system weighting and spectrum efficiency, which may include the following:
  • this embodiment can jointly optimize the uplink and downlink transceivers by calling the concave-convex algorithm optimization relationship, and the concave-convex algorithm optimization relationship can be expressed as:
  • h IUI,j,k is the inter-user interference channel between the kth downlink user and the jth uplink user
  • N is the code length
  • w D,k is the precoding vector of the kth downlink user
  • p U,j is the power consumption of the jth uplink user
  • k′ is the k′th downlink user
  • HD,k is the intermediate parameter
  • hD ,k is the downlink channel between T-APs and the kth downlink user, is the conjugate
  • the value at the nth iteration is the conjugate transpose of h D,l,k , where h D,l,k is the channel vector from the lth T-AP to the kth downlink user, is the value of ⁇ D,k at the nth iteration, is the conjugate transpose of u U,j , u U,j is the combined vector used to demodulate the data signal of the jth uplink user, is the value of u U,j at the nth iteration, is the value of p U,j at the nth iteration, is the variance of the additive white Gaussian noise at the zth R-AP, u U,j,z is the receiver vector of the zth R-AP processing the jth uplink user, is the value of u U,j,z at the nth iteration, H U,j′ is the intermediate parameter, p U,j′ is the power consumption of the j′th up
  • c>0 represent two scalar variables
  • b represents a variable in vector form
  • A represents a matrix variable
  • n represents the number of loops
  • c (n) and b (n) represent the current feasible points of c and b in the nth loop, respectively. It means taking the real part.
  • this embodiment adopts a CCCP-based method (CCCP is a monotonically decreasing global optimization method) to solve the above-mentioned problem of joint optimization design of uplink and downlink transceivers.
  • CCCP is a monotonically decreasing global optimization method
  • a>0, c>0 represent two scalar variables, b represents a variable in vector form, and A represents a matrix variable; n represents the number of loops, and c (n) and b (n) represent the current feasible points of c and b in the nth loop respectively.
  • constraint C17 has been rewritten as a convex constraint, but C16 is still a non-convex constraint, so through some simple changes, C16 is rewritten as follows:
  • Uplink constraint approximation Uplink constraints C8 and C10 are similar to downlink constraints. First, constraint C10 is approximated. After some simple operations, we get:
  • constraint C21 is rewritten as:
  • ⁇ U,j is an auxiliary variable introduced, and ⁇ U,j ⁇ 0 ⁇ , is the value of ⁇ U,j at the nth iteration,
  • the inequality takes the equal sign.
  • constraint C22 After completing the approximate processing of constraint C21, a new auxiliary variable ⁇ U,j,k,l,z ⁇ 0 ⁇ is introduced for constraint C22, so constraint C22 can be equivalently converted into the following two equations:
  • constraints C35-C37 can be approximated as:
  • this embodiment also provides another solution to the joint optimization problem, which can be called a hybrid ZF-MRT beamforming algorithm.
  • This method can jointly optimize the uplink and downlink transceivers by calling the hybrid algorithm optimization relationship.
  • the hybrid algorithm optimization relationship can be:
  • C67: ⁇ , ⁇ ,d k′,k are auxiliary variables, is the merging factor variable, p D,l,k is the power transmitted from the lth T-AP to the kth downlink user when hybrid beamforming is used, is the value of p D,l,k at the nth iteration, is the R-AP set, for The value at the nth iteration, is the value of p U,j at the nth iteration, p U,j is the power consumption of the jth uplink user, represents the second preset function, is the value of d k′,k at the nth iteration, for The value at the nth iteration, represents the first preset function, u U,j is a combined vector for demodulating the data signal of the jth uplink user, is the value of u U,j at the nth iteration, is the conjugate transpose of u U,j , is the value of u U,j,z at the
  • ZM Z*M, where Z and M are both real numbers.
  • Z and M are both real numbers.
  • G k′,k can be rewritten as:
  • the power transmitted by the lth AP to the kth user can be expressed as:
  • the CCCP method can be used to obtain convex approximations of constraints C49, C50, C51, and C52 respectively.
  • constraints C49 and C51 are processed.
  • auxiliary variables ⁇ d k′, k ⁇ 0, ⁇ ⁇ 0, ⁇ ⁇ 0 ⁇ the left side of constraint C49 can be transformed into:
  • constraint C49 can be approximated as:
  • C55, C56, C57 and C58 can be transformed into:
  • the Hybrid in FIG3 corresponds to the technical solution of the present application for joint optimization of uplink and downlink transceivers based on the hybrid beamforming algorithm of CCCP (for ease of description, referred to as Hybrid), the horizontal axis of FIG3 represents the number of iterations, and the vertical axis represents the spectrum efficiency. It can be seen from FIG3 that NAFD can obtain the best steady-state performance, followed by Hybrid.
  • the SE of the three schemes NAFD, Hybrid, and CCFD
  • ⁇ 10dB the spectrum efficiency obtained by NAFD and Hybrid is lower than that of the TDD scheme.
  • FIG8 shows the relationship between SE and the number of antennas M.
  • the embodiment of the present invention also provides a corresponding device for the spectrum efficiency determination method of the non-cellular massive MIMO uRLLC system based on NAFD, which further makes the method more practical.
  • the device can be described from the perspective of functional modules and hardware.
  • the spectral efficiency determination device of the NAFD-based cellular-free massive MIMO uRLLC system provided in the embodiment is introduced.
  • the spectral efficiency determination device of the NAFD-based cellular-free massive MIMO uRLLC system described below and the spectral efficiency determination method of the NAFD-based cellular-free massive MIMO uRLLC system described above can be referenced to each other.
  • FIG9 is a structural diagram of a spectral efficiency determination device for a cellular-free massive MIMO uRLLC system based on NAFD provided by an embodiment of the present invention in a specific implementation manner, and the device may include:
  • the spectrum efficiency determination module 901 is used to determine the uplink and downlink spectrum efficiency based on the maximum decoding error probability of the uplink and downlink users according to the inter-user interference channel of the uplink and downlink users, the channel from the uplink users to the R-APs, the channel from the downlink users to the T-APs, the transmission power of the uplink users and the system noise;
  • the spectrum efficiency optimization module 902 is used to jointly optimize the uplink and downlink transceivers based on the power consumption constraints and service quality constraints of the uplink and downlink users, and determine the target spectrum efficiency by maximizing the uplink and downlink weighted and spectrum efficiencies.
  • FIG. 10 is a structural schematic diagram of an electronic device provided in an embodiment of the present application under one implementation.
  • the electronic device includes a memory 100 for storing a computer program; a processor 101 for implementing the steps of the spectral efficiency determination method of the NAFD-based non-cellular massive MIMO uRLLC system mentioned in any of the above embodiments when executing the computer program.
  • the electronic device may further include a display screen 102, an input/output interface 103, a communication interface 104 or a network interface, a power supply 105, and a communication bus 106.
  • a display screen 102 may further include a liquid crystal display (LCD), a liquid crystal display (LCD), a liquid crystal display (LCD), a liquid crystal display (LCD), a liquid crystal display (LCD), a liquid crystal display (LCD), and a power supply 105, and a communication bus 106.
  • FIG10 only uses one thick line, but does not mean that there is only one bus or one type of bus.
  • FIG. 10 does not limit the electronic device and may include more or fewer components than shown in the figure, for example, may also include a sensor 107 for implementing various functions.
  • the embodiments of the present invention can effectively improve the performance of the NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system to meet the high performance requirements of users for the NAFD-based non-cellular massive MIMO ultra-high reliability and low latency system.
  • the spectrum efficiency determination method of the NAFD-based non-cellular massive MIMO uRLLC system in the above embodiment is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium to execute all or part of the steps of the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM, registers, hard disks, multimedia cards, card-type memories (such as SD or DX memories, etc.), magnetic memories, removable disks, CD-ROMs, magnetic disks or optical disks, and other media that can store program codes.
  • the present application also provides a readable storage medium storing a computer program, which, when executed by a processor, performs the steps of a method for determining the spectrum efficiency of a NAFD-based cellular-free massive MIMO uRLLC system as described in any of the above embodiments.

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Abstract

L"invention concerne un procédé de détermination d'efficacité spectrale de système uRLLC NAFD et un module, qui sont appliqués au domaine technique de la transmission sans fil. Le procédé consiste à : selon un canal d'interférence inter-utilisateur d'utilisateurs de liaison montante et de liaison descendante, des canaux de l'utilisateur de liaison montante à des R-AP, des canaux de l'utilisateur de liaison descendante à des T-AP, la puissance de transmission de l'utilisateur de liaison montante et le bruit de système, déterminer des efficacités spectrales de liaison montante et de liaison descendante sur la base de l'assurance des probabilités d'erreur de décodage maximales des utilisateurs de liaison montante et de liaison descendante ; et, sur la base de contraintes de consommation d'énergie et de contraintes de qualité de service des utilisateurs de liaison montante et de liaison descendante, effectuer une optimisation conjointe sur des émetteurs-récepteurs de liaison montante et de liaison descendante avec l'objectif de maximiser les efficacités spectrales de liaison montante et de liaison descendante, de façon à déterminer une efficacité spectrale cible, améliorant ainsi efficacement les performances du système.
PCT/CN2023/079495 2022-11-28 2023-03-03 Procédé et module de détermination d'efficacité spectrale de système urllc nafd WO2024113524A1 (fr)

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CN202211508485.6A CN115884227A (zh) 2022-11-28 2022-11-28 NAFD uRLLC系统的频谱效率确定方法及组件

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CN113078929A (zh) * 2021-03-18 2021-07-06 东南大学 网络辅助全双工无蜂窝大规模mimo双工模式优化方法
CN114501504A (zh) * 2022-02-23 2022-05-13 国网电力科学研究院有限公司 一种基于无蜂窝网络的联合优化方法及系统
CN115021846A (zh) * 2022-05-23 2022-09-06 浙江师范大学 去蜂窝大规模mimo下行链路频谱效率和能量效率均衡优化方法

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CN113078929A (zh) * 2021-03-18 2021-07-06 东南大学 网络辅助全双工无蜂窝大规模mimo双工模式优化方法
CN114501504A (zh) * 2022-02-23 2022-05-13 国网电力科学研究院有限公司 一种基于无蜂窝网络的联合优化方法及系统
CN115021846A (zh) * 2022-05-23 2022-09-06 浙江师范大学 去蜂窝大规模mimo下行链路频谱效率和能量效率均衡优化方法

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XIA XINJIANG; FAN ZHENQI; LUO WUYANG; LU AN; WANG DONGMING; ZHAO XINSHENG; YOU XIAOHU: "Transceiver Design and Mode Selection for Secrecy Cell-Free Massive MIMO with Network-Assisted Full Duplexing", 2022 IEEE 95TH VEHICULAR TECHNOLOGY CONFERENCE: (VTC2022-SPRING), IEEE, 19 June 2022 (2022-06-19), pages 1 - 7, XP034176151, DOI: 10.1109/VTC2022-Spring54318.2022.9860912 *
XIA XINJIANG; ZHU PENGCHENG; LI JIAMIN; WU HAO; WANG DONGMING; XIN YUANXUE; YOU XIAOHU: "Joint User Selection and Transceiver Design for Cell-Free With Network-Assisted Full Duplexing", IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, IEEE SERVICE CENTER, PISCATAWAY, NJ., US, vol. 20, no. 12, 18 June 2021 (2021-06-18), US , pages 7856 - 7870, XP011892757, ISSN: 1536-1276, DOI: 10.1109/TWC.2021.3088485 *

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