58 results about "Mimo communication systems" patented technology

The invention relates to a memristor array-based MIMO communication system signal detection method, circuit, device and equipment, which are used in the field of wireless communication signal processing. In order to solve the problem that an existing MIMO signal detection calculation circuit based on a memristor array is very sensitive to conductance errors of memristors, an MIMO channel matrix is expressed as a product of a small-scale fading coefficient matrix and a large-scale fading coefficient matrix, and a matrix calculation expression of ZF signal detection and MMSE signal detection is converted into a new equivalent form. A matrix calculation circuit based on the memristor array is used for calculating the converted equivalent expression, and signal detection is achieved; the invention provides two kinds of matrix calculation circuit design schemes based on the memristor array, two kinds of corresponding MIMO communication system signal detection devices and three kinds of MIMO communication system signal detection equipment based on the memristor array. According to the invention, the sensitivity to the conductivity error of the memristor is lower, and the signal detection performance is better.

The invention discloses a resource allocation method of STAR-RIS assisted cellular-free mMIMO (multiple input multiple output). The method comprises the following steps: acquiring position information of UE, AP and STAR-RIS, acquiring channel state information (CSI) of each communication link, and constructing a state information set of a current system based on the position information and the CSI; based on the state information set, utilizing an Actor network in a depth deterministic policy gradient (DDPG) algorithm to generate an optimization action; adjusting resources among the UE, the AP and the STAR-RIS on the basis of the optimization action, performing downlink signal transmission on the basis of the adjusted resources, and calculating the outage probability, the SINR and the information transmission rate per unit time of the UE; and outputting an instant reward value under the optimization action based on the outage probability, the SINR and the information transmission rate, and performing updating optimization based on the instant reward value. According to the invention, the technical problem of poor performance of a traditional cellular-free large-scale MIMO communication system is solved.

The present invention discloses a method for modeling ultra-large-scale MIMO geometric random and beam-domain wireless channels, and the specific steps include: 1) setting simulation parameters, network layout, etc., generating initial large-scale parameters, and generating initial clusters based on model initialization parameters; 2) updating large-scale and small-scale parameters; 3) generating geometric random channel model channel coefficients, steering matrices, and beam-domain channel matrices; 4) analyzing channel characteristics, and verifying the accuracy of the model by comparing with measured data. The wireless channel modeling method established by the present invention supports spherical waves and spatial non-stationary characteristics, and can realize the conversion from geometric random to beam-domain channel models under near-field conditions. The model accuracy is verified by the consistency of simulation and measurement results of space-time-frequency correlation functions and channel capacity. The present invention has guiding significance for the design and performance evaluation of ultra-large-scale MIMO communication systems.

The present invention belongs to the technical field of wireless communications, and particularly relates to a beamforming and user selection method based on a distributed IRSs-aided MIMO communication system. The method comprises: constructing a distributed IRSs-aided MIMO communication system model; constructing a joint optimization problem P for active beamforming at a base station, phase shifts of IRSs, and a user selection strategy; decoupling the joint optimization problem P into a joint optimization subproblem P1 for a user selection strategy and active beamforming at the base station, and an optimization subproblem P2 for phase shifts of the IRSs; solving the joint optimization subproblem P1 to obtain a user selection strategy and a beamforming vector at the base station; solving the optimization subproblem P2 to obtain phase shifts of the IRSs; and repeatedly executing the solving steps until the joint optimization problem P converges, so as to obtain an optimal user selection strategy, an optimal beamforming vector at the base station, and optimal phase shifts of the IRSs, and then executing same. While ensuring the user service quality, the present invention significantly reduces the transmitting power of a base station, thereby improving the system performance.

A method and system are provided for scheduling data transmission in a Multiple-Input Multiple-Output (MIMO) system. The MIMO system may comprise at least one MIMO transmitter and at least one MIMO receiver. Feedback from one or more receivers may be used by a transmitter to improve quality, capacity, and scheduling in MIMO communication systems. The method may include generating or receiving information pertaining to a MIMO channel metric and information pertaining to a Channel Quality Indicator (CQI) in respect of a transmitted signal; and sending a next transmission to a receiver using a MIMO mode selected in accordance with the information pertaining to the MIMO channel metric, and an adaptive coding and modulation selected in accordance with the information pertaining to the CQI.

The invention discloses a non-orthogonal polarization MIMO (Multiple Input Multiple Output) communication system, which belongs to the technical field of wireless communication and comprises a serial-parallel conversion and precoding module, a signal distribution network, a transmitting channel, a non-orthogonal transmitting array antenna, a non-orthogonal receiving array antenna, a receiving channel, a signal merging network and an MIMO signal detection module, a non-orthogonal transmitting antenna unit is arranged in the non-orthogonal transmitting array antenna, and a non-orthogonal receiving antenna unit is arranged in the non-orthogonal receiving array antenna. According to the invention, parallel transmission of multiple paths of signal streams can be realized under various channel conditions, and the transmission rate and the spectrum utilization rate of the system are improved.

Methods and apparatus for indicating unequal modulation (UEQM) parameters for spatial streams between antennae of multiple input, multiple output (MIMO) communication systems are provided. Embodiments enable UEQM by introducing a high-throughput control (HTC) extension field in the medium access control header of data frames. The HTC extension field can include modulation parameters for each of a plurality of spatial streams as well as link adaptation parameters for the communication system. In some embodiments, changes in modulation parameters between consecutive spatial streams are used to indicate the modulation parameters for each spatial stream. In some other embodiments, indices for common combinations of modulations are used to indicate the respective modulation parameters for each spatial stream. UEQM enabled by embodiments may provide an improved throughput and goodput to MIMO communication systems.

The invention provides a decentralized graph neural network architecture for multi-cell multi-user MIMO communication system beam forming, and the construction steps of the architecture comprise: step 1, in a method for optimizing the multi-cell multi-user MIMO communication system beam forming by using a graph neural network, constructing a local loss function of a base station, and realizing computational graph decoupling; step 2, constructing a heterogeneous graph model based on the local loss function of the base station proposed in the step 1, and realizing decoupling of a graph model level; and step 3, carrying out distributed training and reasoning on the heterogeneous graph model to obtain a decentralized graph neural network architecture oriented to multi-cell multi-user MIMO communication system beam forming.

The invention relates to a task-driven MIMO image processing method and device based on machine consciousness, computer equipment, a computer readable storage medium and a computer program product, and the method comprises the steps: obtaining image data which comprises a sample image and annotation data; performing feature encoding processing on the sample image through an encoder to obtain a target feature, and performing dimension reforming on the target feature to obtain a target number of paths of MIMO data streams; performing uniform quantization based on a preset bit number to obtain a communication baseband symbol corresponding to the bit stream; transmitting through a communication channel, and receiving a communication baseband symbol through a receiving end to obtain a target recovery feature; performing feature decoding and task prediction through a decoder and a task processing module to obtain prediction data; training is carried out based on the prediction data and the annotation data, a trained image processing model is obtained, and deep coupling of an actual digital MIMO communication system and an intelligent agent perception task is achieved.

The invention discloses a channel acquisition method and system for a reconfigurable MIMO communication system, and belongs to the technical field of wireless communication, and the method comprises the steps: selecting any one directional diagram from all reconfigurable directional diagrams of a transmitting end, enabling all antennas of the transmitting end to use the selected directional diagram, and estimating a channel corresponding to the selected directional diagram; all reconfigurable antennas of a transmitting end are grouped according to the number of reconfigurable directional diagrams, so that different grouped antennas use different directional diagrams, antennas in the same group use the same directional diagram, and channels corresponding to each group of directional diagrams are estimated; and obtaining an estimated channel path and corresponding angle information based on the estimated channel, and extrapolating channel state information corresponding to all directional diagrams. According to the invention, after the partial channel state information of the directional diagrams is estimated through a small amount of pilot signals, the channel state information corresponding to all the directional diagrams is extrapolated by using the estimated partial channel state information, so that the pilot overhead is effectively reduced.

The present invention discloses an OSIC detection method for an underwater optical Massive MIMO communication system with misaligned transmission and reception. After estimating the gain of each sub-channel using the LS channel estimation algorithm, the offset direction of the transceiver can be determined based on the magnitude of each DC gain in the channel gain matrix. The detection column order and the order within the column are then determined based on the offset direction, and interference elimination is performed to complete the detection of each signal. The present invention sorts according to the offset direction, preferentially detecting signals without interference, and then detecting signals with interference, greatly reducing the error propagation caused by the sorting, making the subsequent stage more accurate in subtracting the detected signal, and making the remaining signal used in the subsequent stage have less interference, thereby improving the bit error rate performance, so as to solve the problem of increased bit error rate of the UWOC system caused by misalignment of the transceiver and offset and diffusion of the imaging spot in the underwater imaging optical Massive MIMO communication system.

The invention discloses a super-large-scale MIMO communication system, a user scheduling method thereof and a medium, and relates to the technical field of MIMO communication systems.The method comprises the steps that a channel model containing a spherical wave propagation model is established in a near-field communication scene, and the near-field propagation characteristic that the antenna array size is equivalent to the user distance is considered; obtaining a beam focusing vector of the user based on a channel model; calculating to obtain beam focusing vectors and correlation between the beam focusing vectors; using an alternative optimization algorithm to jointly optimize user scheduling and power distribution, including grouping the users based on the correlation, so that the users in each group have similar channel conditions; and the total spectrum efficiency of the system is maximized under the condition that the minimum spectrum efficiency constraint and the total transmitting power constraint are met. According to the invention, interference among users can be effectively reduced, and the accuracy and efficiency of user scheduling can be improved by an alternative optimization scheduling method.

A signal restructure unit for radio frequency (RF) antenna systems includes four ports and a signal routing circuit. The signal routing circuit receives RF signals at input ports and provides phase-controlled outputs to antenna ports. When receiving sum signals, the unit provides in-phase restructured signals for common-mode antenna operation. When receiving difference signals, the unit provides anti-phase restructured signals for differential-mode antenna operation. The signal routing circuit may be implemented as a rat-race coupler with transmission line segments or as discrete circuit elements including inductors and capacitors. An RF communication system incorporates the signal restructure unit with digital processing circuits, transceivers, and antennas to achieve MIMO operation from a single antenna structure. The system provides improved isolation while reducing the antenna size. The restructure unit enables reconfigurable MIMO operation with enhanced performance for wireless communication applications.

The present invention provides a multi-RIS-assisted semi-blind joint channel estimation and symbol detection method and system. The solution includes establishing a multi-RIS-assisted MIMO communication system model; establishing a signal received by a base station as a parallel factor tensor model; converting the channel estimation and symbol detection problem into an iterative optimization problem of a cost function based on a tensor expansion; and solving the cost function through ALS. The solution solves the problem of excessively high dimensionality of received signals due to the multiplication of the number of RIS reflection elements in multi-RIS-assisted communication scenarios, making it difficult to accurately and quickly obtain channel state information. Compared with the pilot-assisted ALS algorithm and the KAKF semi-blind receiver in single-RIS-assisted communication scenarios, the method can effectively improve estimation accuracy and reduce bit error rate and pilot overhead.

Disclosed in the present disclosure are signal processing methods, an apparatus, a system, a storage medium and a computer program product. A method is applied to a network device, the method comprising: receiving first indication information reported by a terminal device; on the basis of the first indication information, configuring a demodulation reference signal for the terminal device; on the basis of the first indication information, the demodulation reference signal and data to be transmitted, generating a downlink signal; and transmitting the downlink signal to the terminal device. The present disclosure solves the problem that because of relatively low antenna switching speed of terminals, existing MIMO communication systems are prone to produce ICI during downlink transmissions and thus result in deterioration of the demodulation performance of receivers.

The invention discloses an optimization method, system and device combining antenna selection and precoding, and a storage medium, and belongs to the technical field of wireless communication. The method comprises the following steps: acquiring communication data from a base station to a user in a target XL-MIMO communication system; calculating a received signal of the user based on the communication data; based on the received signal, constructing a joint optimization model which takes the maximum sum rate as an optimization target and takes an antenna selection matrix and a hybrid precoding matrix at a base station as optimization variables; decomposing a solving problem of the joint optimization model into sub-problems by adopting an alternating direction method; alternately solving the sub-problems to obtain an optimization result; and obtaining an antenna selection matrix and a hybrid precoding matrix at the base station according to an optimization result. According to the method, the antenna selection problem is converted from integer programming to matrix sparsity optimization by adopting the alternating direction method, the constraint optimization problem of key variables is effectively solved, and the spectrum efficiency of a communication system is improved.

An electronic device which includes processing circuitry configured to acquire training data corresponding to multiple antennas, the training data having a label and features, the label including a first channel value for a first time slot, and the features including a plurality of second channel values for a plurality of time slots before the first time slot, train a channel prediction model based on the training data to obtain a trained channel prediction model, and obtain a channel prediction value for a prediction time based on the trained channel prediction model.

The invention discloses a channel estimation method and device based on an MU-MIMO communication system, which are used for improving the accuracy of channel estimation in an MU-MIMO communication scene in which a plurality of terminal devices with different time bias communicate at the same time. The method is applied to network side equipment, the network side equipment is connected with multiple pieces of terminal equipment UE, and the multiple pieces of UE multiplex the same time-frequency resource. The method comprises the following steps: performing channel estimation based on a signal received on a time-frequency resource to determine an initial channel matrix, and determining a time offset value of each UE based on the signal; performing time offset correction on the initial filter according to the time offset value of the first UE, and determining a target filter of the first UE; the first UE is any UE in the plurality of UEs; and filtering the initial channel matrix by using a target filter of the first UE to obtain a target channel matrix of the first UE.

The invention provides a capacity improvement method and system based on intelligent metasurface near field deployment, and the method comprises the steps: a deployment step: symmetrically deploying RIS of an RIS-assisted MIMO communication system, and obtaining a deployed MIMO communication system; the RIS is an intelligent metasurface; and an optimization step: constructing a joint optimization problem according to the deployed MIMO communication system, solving the joint optimization problem, obtaining an optimal RIS phase shift vector and power distribution vectors of all users, and further optimizing the MIMO communication system. According to the method, the calculation complexity of system design and online operation is remarkably reduced, and the feasibility of actual deployment in a large-scale system is achieved.

The invention relates to the technical field of wireless communication, and provides a channel estimation method and system based on super-large-scale MIMO near-field channel block sparsity, a terminal and a medium. The channel estimation method comprises the following steps: mining burst non-uniform block sparsity of a near-field channel in a polar domain based on dynamic appearance and disappearance characteristics of a channel in a hybrid precoding super-large scale MIMO communication system based on uplink time division duplex in a spatial non-stationary state and a scattering cluster; the improved structure coupling prior is adopted to reflect the structured sparsity; and performing channel estimation by using a Bayesian optimal memory approximate message passing algorithm. According to the method, the channel estimation precision in a super-large-scale MIMO near-field scene can be improved.

A vehicle-mounted system may include a first plurality of antennas, a second plurality of antennas, and one or more circuits configured for handling signals transmitted and / or received via the first plurality of antennas and the second plurality of antennas. At least two antennas of the first plurality of antennas have antenna patterns in different directions. At least two antennas of the second plurality of antennas have antenna patterns in different directions. At least one antenna of the first plurality of antennas and at least one antenna of the second plurality of antennas have antenna patterns in a same first direction. At least one other antenna of the first plurality of antennas and at least one other antenna of the second plurality of antennas have antenna patterns in a same second direction that is different than the first direction.

The present invention relates to a MIMO communication system signal detection method, circuit, device, and apparatus based on a memristor array, which are used in the field of wireless communication signal processing. To address the problem that existing MIMO signal detection calculation circuits based on memristor arrays are extremely sensitive to memristor conductance errors, the present invention represents the MIMO channel matrix as the product of a small-scale fading coefficient matrix and a large-scale fading coefficient matrix, transforms the matrix calculation expressions for ZF signal detection and MMSE signal detection into a new equivalent form, and uses a memristor array-based matrix calculation circuit to calculate the transformed equivalent expression to achieve signal detection. The present invention provides two memristor array-based matrix calculation circuit design schemes, two corresponding MIMO communication system signal detection devices, and three memristor array-based MIMO communication system signal detection devices. The present invention is less sensitive to memristor conductance errors and has better signal detection performance.

The present application relates to the field of wireless communication physical layer security technology, especially to a MIMO communication system radio frequency fingerprint protection method based on structured disturbance. The method first acquires a communication signal to be sent and a pre-shared key, generates a disturbance parameter based on the pre-shared key and a data packet index; uses a first disturbance factor to independently perform weighting processing on a training sequence in the communication signal in the dimension of a transmission antenna, maintains the spatial orthogonal structure among multi-antenna signals; performs structured linkage disturbance processing on a data symbol in the communication signal, establishes a disturbance association between the data symbol and the training sequence; and sends the communication signal after the weighting processing and the structured linkage disturbance processing through a wireless channel. The present application can effectively hide the radio frequency fingerprint to prevent device tracking, maintain the spatial orthogonality of the MIMO preamble, and realize the recoverable authentication of the cooperative receiver and the transparent compatibility of the non-cooperative standard receiver.

The application relates to an active intelligent super-surface assisted MIMO communication system control method, a communication system comprising a base station, an active intelligent super-surface and a plurality of user terminals, a direct link between the base station and the user terminals being blocked by an obstacle, the method comprising: establishing a received signal model and a quantization noise model at the base station, and obtaining an uplink rate of each user terminal and a sum rate of all users; performing signal processing at the base station by using maximum ratio combining and an analog-to-digital converter with a precision lower than a preset threshold; establishing an active intelligent super-surface phase shift optimization problem according to the received signal model and the uplink rate, solving the optimization problem to obtain an optimal phase shift matrix, and controlling the active intelligent super-surface to operate according to the optimal phase shift matrix. Compared with the prior art, the application can overcome the multiplicative fading effect of a passive intelligent super-surface, and the problem of reduced communication performance caused by an undesirable phase shift, improve the communication system performance, and reduce system energy consumption and hardware cost.

This invention belongs to the field of wireless communication technology, specifically relating to a SIM-enabled massive MIMO communication system. The system employs a single-RF link transmitter architecture, replacing traditional antenna arrays and single-layer reconfigurable smart surfaces with a SIM, enabling efficient signal transmission in multi-user communication scenarios. Specifically, the stacked smart metasurface applies controllable phase modulation to the incident single-frequency carrier signal, achieving signal modulation and precoding without the need for traditional baseband modulation. This allows different users to receive their desired signals with low mutual interference. Compared to traditional massive MIMO systems, this system architecture effectively alleviates the engineering challenges of high hardware complexity, high integration density, increased power consumption, and limited heat dissipation faced by high-frequency communication, while significantly reducing reliance on high-precision digital-to-analog converters and multiple RF links.

The invention provides a physical layer authentication method for a massive MIMO communication system. The method comprises the following steps: an expected receiver determines a test statistic Lx used for evaluating channel state information difference between adjacent time intervals through a log-likelihood ratio; and when the sender is the legal user equipment and assumed H0, when the sender is the attacker and assumed H1, and when Lx is smaller than or equal to a threshold value delta, the expected receiver accepts the assumed H0 and judges that the sender is the legal user equipment, otherwise, the expected receiver accepts the assumed H1 and judges that the sender is the attacker. According to the authentication scheme, modeling is carried out on a channel in a massive MIMO antenna communication scene, and the influence of antenna coupling, antenna space correlation and the like caused by antenna element spacing reduction and antenna data increase on the physical layer authentication performance is measured. And the PCA and the SVD are used for carrying out spatial domain and frequency domain decorrelation on the high-dimensional channel information, so that the storage space occupied by the channel information at a base station end can be reduced, and the authentication overhead is greatly reduced under the condition that the same authentication performance is ensured.

The invention discloses a pre-coding matrix determination method and device, network equipment and a storage medium, and the method comprises the steps: updating or determining a pre-coding matrix of an FDD frequency band according to a pre-coding matrix of a first TDD frequency band in a multi-frequency-band MIMO communication system which supports TDD and FDD at the same time; wherein the first TDD frequency band represents a TDD frequency band adjacent to the FDD frequency band.

The invention relates to the technical field of wireless communication, and discloses a multi-user downlink scheduling method and computer equipment. Comprising the following steps: acquiring a large-scale channel coefficient from each user equipment to each far-end radio frequency unit in the distributed base station; determining a multi-user signal to interference and noise ratio of the user equipment on the allocated sub-band by using the large-scale channel coefficient and interference and noise of the user equipment on the corresponding sub-band; determining a target modulation coding strategy of the user equipment by using the multi-user signal to interference plus noise ratio so as to execute downlink transmission operation; wherein the target modulation coding strategy is used for describing a transmission parameter of the user equipment on the allocated sub-band. Therefore, the key channel characteristics are reserved while the calculation complexity is reduced, the MU-SINR is calculated in combination with sub-band level interference and noise, the actual channel quality in a multi-user coexistence scene can be accurately reflected, channel utilization and interference control are optimized, and the communication performance and resource efficiency of a cellular-free large-scale multiple-input-multiple-output communication system are greatly improved.

The present invention discloses a method for close-range ultraviolet light detection and identification of anti-UAVs in three-dimensional space, comprising: rotating an ultraviolet MIMO communication system to detect and obtain a target UAV's position signal; the ultraviolet MIMO communication system includes an array of ultraviolet light sources; determining whether the position signal is a UAV signal; and if so, determining whether the UAV signal is a friendly UAV to complete identification. The ultraviolet MIMO communication system (ultraviolet photoelectric detector) is used for detection, identification, and communication, with long-term stable detection accuracy and strong anti-interference capabilities against infrared, visible light, and electromagnetic interference. After classifying and identifying the target UAV, an electronic password query method is used to further determine whether it is a friendly UAV, thereby improving identification accuracy. At the same time, covert communication continues to complete information exchange between UAVs.

A method for reducing peak-to-average power ratio, PAPR, in a Multiple Input Multiple Output, MIMO, communication system is disclosed. The method is performed in a precoder unit and includes: confining, by a differentiable cost function, power of a MIMO signal to be between a lower threshold, Plow, and an upper threshold, Pup, and applying a gradient method on the differentiable cost function until reaching a set power target for the MIMO signal, while keeping an Error Vector Magnitude, EVM, below a set EVM level.