Joint Scheduling and Precoding Based on SLNR Criteria in MU-MIMO System

Abstract

The user scheduling and precoding schemes in Multi-User Multiple Input Multiple Output (MU-MIMO) system have the problem of high complexity and the performance of traditional criteria is not good. This paper analysis the advantages of Signal to Leakage plus Noise Ratio (SLNR) criteria firstly, then propose a cross-layer design of user scheduling and precoding scheme based on SLNR criteria. The design only uses SLNR criteria and includes an improved SLNR user scheduling scheme which is accomplished by iteration procedure. Numerical results verify the improved user scheduling scheme can improve the performance of sum capacity and average BER and the cross-layer design has lower complexity.

SLINR-Based Downlink Optimization in MU-MIMO Networks

“…kb , with α f denoting the forgetting factor. Throughout this section, the proposed algorithm used Pr (u k ′ b ′ = 1) = M t /K b , i.e., we assumed all users in neighboring cells were equally likely to be scheduled (see (15)).…”

“…This algorithm iterates between designing optimal beamforming vectors given the current set of scheduled users, then refining the optimal set of users given the current beamforming vectors; this procedure converges to a stationary point. SLNR-Based Optimization: SLNR-based approaches for resource allocation have garnered some interest [10], [11], [12], [13], [14], [15]. The fundamental benefit is that optimizing an SLNR-based function requires only local CSI.…”

“…This lower bound loosens when the number of users is much greater than the number of antennas, and so they also propose a successive scheduling algorithm, which incrementally schedules the best user given previous scheduling decisions. In [15], a mixed approach is proposed with one half of the users scheduled using the max-lower bound criterion and the other half using successive scheduling. The authors also propose power allocation based on the SLNR computed for each user.…”

“…In other words, real-time knowledge of the scheduling variables is not necessary as long as the impact this has on the intercell leakage computation is small. Regardless of how the probabilities are assigned, by relaxing our knowledge of the scheduling variables in neighbouring cells to probabilities, we obtain a decentralized way of evaluating a beam's intercell leakage via (15); thus, BSs are fully decoupled.…”

“…Here, Linter kb (ν nb ) and Linter kb (ν nb ) are identical to (15) and (20), respectively, except that ν nb is used in the calculation instead of v kb . With the previous equations in mind, VOLUME 4, 2016 we can see that the SLINR for this user can be written as…”