A Joint Algorithm of Continuous Precoding and User Selection for Multi-user MIMO Broadcast Channel

Abstract

The invention discloses a continuous precoding and user selection joint algorithm of a multi-user MIMO broadcast channel, which is the normalized projection of the precoding vectors of all unselected users to the orthogonal complement space formed by the precoding vectors of all selected users The vector is used as the new precoding vector of the user, and the user is selected according to the signal to interference plus noise ratio of each user, and one user is selected at a time until the preset number of users is reached, so as to obtain the best precoding vector for each selected user . The invention has low algorithm complexity, can effectively suppress multi-user interference, and improves channel capacity compared with the traditional method, and can effectively improve system performance especially in the case of large number of users and high signal-to-noise ratio.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and more specifically relates to a continuous precoding and user selection joint algorithm of a multi-user MIMO broadcast channel. Background technique [0002] Under the multi-user MIMO (Multiple-Input Multiple-Output, multiple-input multiple-output) downlink broadcast channel model based on limited feedback, in order to achieve spatial multiplexing and improve data transmission rate, the base station often selects multiple users to communicate at the same time, multi-user MIMO The technology uses the spatial freedom provided by multiple antennas to separate users, each user can occupy the same time-frequency resource, and the average throughput of the cell can be effectively improved through time-frequency resource multiplexing. When the cell load is heavy, a simple multi-user scheduling algorithm can obtain significant multi-user multiplexing gain, which is an effective means to o...

AI Technical Summary

Problems solved by technology

However, the DPC algorithm requires perfect channel estimation at the base station, and the high complexity caused by the full search of all user combinations when selecting users also makes this algorithm unsuitable for practical communication systems

[0004] The other is a genetic and greedy user scheduling algorithm based on continuous ZF (zero forcing) precoding. Although this algorithm reduces the complexity of user scheduling, it still requires the base station to perfectly obtain channel state information.

In addition, an algorithm based on SLNR (Signal to Leakage Plus Noise Ratio, Signal to Leakage Plus Noise Ratio) is proposed, which only requires the user to feed back a limited number of bits to represent the channel state information, and maximizes SLNR as the objective function of user scheduling and pre-planning. Coding scheme, this SLNR-based algorithm has the advantages of low complexity and easy implementation, but so far there is no relevant literature to prove that SLNR has a direct relationship with system capacity, so this algorithm cannot maximize system throughput, and in channel estimation In the case of large errors, its performance degrades rapidly

The other is a joint user pairing and precoding algorithm based on SINR (Signal to Interference plus Noise Ratio) estimation. This algorithm has better performance under the condition of imperfect channel estimation, but it simplifies precoding. In the process of encoding vector design, when the first selected user is obtained, the precoding vectors of all other users are determined, and the initial precoding vector direction of other users is not considered, which leads to a part of capacity loss

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