36results about How to "High spectral efficiency" patented technology

The invention provides a multi-user MIMO uplink energy efficiency spectral efficiency joint optimization method assisted by an intelligent reflecting surface. In the method, a user sending signal is received by a base station after being reflected by an IRS, and a reflection unit of the IRS can change the phase of an incident signal. According to the method, part of channel state information is utilized, two different conditions that IRS reflection coefficients can be continuously valued and discretely valued are considered at the same time, and the IRS reflection coefficients can be continuously valued and discretely valued through an alternate optimization method, a deterministic equivalence principle, a secondary penalty method, an MM method, an accelerated projection gradient descent method and the like. And the precoding matrix of each user and the weighted sum of the reflection coefficient maximization energy efficiency and the spectral efficiency of the IRS are jointly designed.And when the channel state information changes, the central controller dynamically implements energy efficiency spectral efficiency joint optimization multi-user MIMO uplink transmission power distribution and IRS reflection coefficient adjustment. The method is low in implementation complexity, can effectively improve the energy efficiency and spectral efficiency of multi-user MIMO uplink communication, and achieves the balance between the energy efficiency and spectral efficiency.

The embodiment of the invention provides a resource allocation method and device. The method comprises the steps of determining an initial subcarrier pairing rule in a current communication network; determining an initial codebook allocation rule and an initial power allocation rule; determining a middle subcarrier pairing rule; calculating a first weight and rate; judging whether an absolute value of the difference between the first weight and rate and the initialized first weight and rate is greater than a first error value or not; if the absolute value is greater than the first error value, determining the middle subcarrier pairing rule as the initial subcarrier pairing rule, determining the first weight and rate as the initialized first weight and rate, and returning to the step of determining the initial codebook allocation rule and the initial power allocation rule; and if the absolute value is not greater than the first error value, determining the initial codebook allocation rule, the initial power allocation rule and the middle subcarrier pairing rule as the optimum codebook allocation rule, the optimum power allocation rule and the optimum subcarrier pairing rule. Through application of the embodiment of the invention, dense communication in a single relay network can be realized.

The invention provides a large-scale MIMO (Multiple Input Multiple Output) safe multicast transmission power distribution method with optimal energy efficiency based on statistical channel state information. The method is used for using a large-scale antenna array and the statistical channel state information. Public signals transmitted by a base station are transmitted to a plurality of legal target users in a multicast mode, an eavesdropper eavesdrops in a transmitting area, the base station obtains statistical channel state information of all the users and the eavesdropper in the transmitting process, multicast transmission power distribution with the optimal energy efficiency is implemented. A series of convex optimization sub-problems are solved through two-layer iteration by utilizing a Minorize Maximize method, Dinkelbach transformation and determinacy so as to obtain a beam domain power distribution matrix of safe multicast. When statistical channel state information between the base station and each user as well as between the base station and an eavesdropper changes, the base station can dynamically implement safe multicast transmission power distribution with optimal energy efficiency, the complexity is low, and the energy efficiency of large-scale MIMO safe multicast transmission can be effectively improved.

The invention provides a high-spectral-efficiency secure-truncation orthogonal frequency division multiplexing transmission method and relates to the technical field of information and communication.The method comprises the steps of inputting a bit information sending sequence I into a transmitter based on IFFT, outputting a time domain sending signal s, and carrying out random truncation on thetime domain sending signal through utilization of a security matrix theta, and sending the signal; and receiving a signal vector y by a receiver based on FFT under the condition that the theta is known, obtaining a frequency domain observation signal vector Y, carrying out V times of ICI interference suppression on the Y, finishing iteration, obtaining a received signal vector Y^caret, and outputting an estimated value S^caret through hard decision based on the Y^caret, passing a demodulator by the S^caret and then outputting the estimated value I^caret of the bit sending sequence, wherein one-time ICI interference suppression comprises the process of adding the frequency domain observation signal vector Y and currently obtained interference estimation -CS<v>-tilde to obtain the received signal vector Y^caret, obtaining the estimated value S<v>-tilde of the bit information sending sequence through the hard decision based on the obtained received signal vector Y^caret, and carrying outICI estimation on the estimated value S<v>-tilde to obtain the interference estimation -CS<v>-tilde. According to the method, the error performance of the receiver of a legal user is improved.

The invention proposes a large-scale MIMO downlink beam domain power allocation method for joint optimization of energy efficiency and spectral efficiency. In this method, the base station configures a large-scale antenna array, and generates a large-scale beam set covering the entire cell through beamforming to serve multiple users at the same time. The base station implements power allocation based on the statistical channel state information of each user to jointly optimize energy efficiency and spectral efficiency. The goal of power allocation optimization is to satisfy the system power constraints and maximize the weighted sum of energy efficiency and spectral efficiency. Using the deterministic equivalence principle and MM method, iteratively solve a series of quasi-concave optimization problems to obtain a locally optimal power allocation matrix. In each iteration process, the quasi-concave optimization problem is decomposed into an inner layer optimization problem to find the optimal power allocation matrix to maximize the system and rate under a given transmission power, and an outer layer optimization problem to solve the optimal transmission power Optimization. The invention has low implementation complexity, can effectively improve the energy efficiency and spectrum efficiency of massive MIMO downlink communication, and realize the balance between the two.

The invention discloses a massive MIMO multicast power distribution method with joint optimization of energy efficiency and spectrum efficiency. That is, multicast signals are sent to users on the same time-frequency resources at the same time. Through the uplink channel sounding process, the base station obtains the statistical channel state information of each user, and uses the weighting factor to implement the multicast transmission power allocation that optimizes system resources (ie, maximizes the weighted sum of energy efficiency and spectral efficiency). The invention has low implementation complexity, and can effectively balance the energy efficiency and spectrum efficiency of massive MIMO multicast transmission to obtain maximum resource efficiency.

The invention discloses a multi-user cognition MIMO interference channel distributed energy efficiency optimization method, comprising the steps of establishing a cognition user energy efficiency maximization target function according to the power limitation and interference threshold limitation of a cognition user, performing equation transformation on the cognition user energy efficiency maximization target function, removing all coupling relationships of the cognition user generated by interference threshold limitation, removing limitation conditions in a cognition user decoupling equivalent energy efficiency maximization target function by using a Lagrange method to obtain a cognition user extended type decoupling equivalent energy efficiency maximization target function, computing the optimal power value of the cognition user through convex optimization by using a matrix decomposition theory, and finally obtaining the optimal energy efficiency value of the cognition user. According to the multi-user cognition MIMO interference channel distributed energy efficiency optimization method provided by the invention, the spectrum effect as well as the energy efficiency of the system can be improved, and thereby the feasibility in practical application can be enhanced.

The embodiment of the invention provides a resource allocation method, a resource determination method, network equipment and a terminal. The resource allocation method comprises the following steps: downlink control information (DCI) is sent to a terminal, the DCI carries first indication information and second indication information, the first indication information is used for indicating M modulation and coding strategies (MCS), the second indication information is used for indicating all frequency domain resources used by one or M physical downlink shared channels (PDSCH), m is an integer greater than or equal to 1. According to the scheme of the invention, the DCI overhead is effectively reduced; and the spectrum efficiency is improved.

The invention provides a determining method and device for macro and micro base station arrangement, and relates to the field of mobile communication. The networking manner between a macro base station and micro stations within the coverage range of the macro station is determined; and according to the determined networking manner, corresponding system spectrum-effect constraint and an edge user coverage constraint; a preset algorithm to determine the system efficacy, the emission power of the micro stations for determining the system efficacy and the amount of the micro stations which need arrangement are iterated till a parameter pair composed of the emission power and the amount of the micro stations is determined, and the system efficacy determined by the parameter pair is highest on the premise that the parameter pair satisfies the constraints, namely the emission power and the amount, of the micro stations, forming the parameter pair satisfy the system spectrum-effect constraint, and the amount of the micro stations satisfies the edge user coverage constraint; and the determined parameter pair is used to arrange the micro stations within the coverage range of the macro station. Compared with the prior art, the method and device are more reasonably.

The invention discloses a method for maximizing minimum energy efficiency multi-cell large-scale MIMO beam domain power allocation. The method includes the following steps: constructing a cell cluster and configuring an antenna array, and generating a beam set through beamforming; Statistical channel state information: Send the statistical channel state information to the central processing center, and perform multi-cell massive MIMO beam domain power allocation: dynamically implement multi-cell massive MIMO beam domain power allocation according to changes in statistical channel state information. The present invention effectively improves the energy efficiency and spectral efficiency through a large-scale antenna array, and fully utilizes the beam domain statistical channel state information of multiple cell users, improves the design performance, and maximizes the minimum energy efficiency in the multi-cell large-scale MIMO beam domain Power allocation, significantly reducing the complexity of optimization problem solving and physical layer implementation.

The invention discloses an online robust distributed multi-cell large-scale MIMO precoding method. The method comprises the following steps that a cell cluster is constructed, antenna arrays are configured, and a beam set is generated through beam forming; base stations dynamically obtain statistical channel state information of users in cells; and each base station performs online multi-cell distributed large-scale MIMO beam domain power allocation by using a deterministic equivalent method, Charnes-Cooper transformation and an online gradient rising algorithm: in each stage of statistical channel state information changes, a power allocation matrix of the next stage is predicted according to all the channel state information obtained in the stage and the previous stages. According to the method, the energy efficiency of a system is effectively improved, the backhaul overhead is reduced by adopting distributed multi-cell cooperation, online precoding transmission can be carried out when channel state information changes, and certain robustness on channel estimation errors is achieved.

The invention discloses a reconfigurable intelligent surface-assisted multi-user MISO downlink wireless communication energy efficiency and spectrum efficiency joint optimization method, which comprises the following steps: in the multi-user MISO downlink transmission, a base station sends a signal to the reconfigurable intelligent surface, which can Reconstruct the path to the user after reflection from the smart surface, as well as the path directly from the base station to the user; based on the joint optimization of energy efficiency and spectrum efficiency as a criterion, the precoding matrix of the base station and the reflection coefficient matrix of the reconfigurable smart surface are jointly optimized; the energy efficiency The goal of joint spectral efficiency optimization is to maximize the weighted sum of system energy efficiency and spectral efficiency under the constraints of base station transmission power; the present invention realizes base station side precoding matrix and RIS through alternate optimization, Quadratic transformation, WMMSE transformation and convex optimization algorithm Joint optimization of reflection coefficient matrices. The invention has low algorithm complexity, can effectively improve the energy efficiency and spectrum efficiency of multi-user MISO downlink communication, and realize the balance between the two.

The invention proposes a large-scale MIMO non-orthogonal unicast multicast transmission power allocation method with optimal energy efficiency. In this method, the base station generates a large-scale beam set covering the entire cell through beamforming, and performs non-orthogonal unicast and multicast communication with users, that is, simultaneously sends unicast and multicast signals to users on the same time-frequency resource . Through the uplink channel detection process, the base station obtains the statistical channel state information of each user, and implements non-orthogonal unicast multicast transmission power allocation with optimal energy efficiency. The algorithm mainly uses deterministic equivalence principle, MM method and Dinkelbach transform to solve a series of convex optimization sub-problems through two layers of iteration to obtain unicast and multicast beam domain power allocation matrices respectively. When the statistical channel information between the base station and each user changes, the base station can dynamically implement non-orthogonal unicast multicast transmission power allocation with optimal energy efficiency. The invention has low implementation complexity and can effectively improve the energy efficiency of large-scale MIMO non-orthogonal unicast multicast transmission.