MIMO broadcast scheduling using binary spider monkey optimization algorithm

Abstract

Summary Multi‐user multiple‐input multiple‐output (MU‐MIMO) system has the capability of delivering optimal system capacity that provides the simultaneous service to a large number of users using dirty paper coding (DPC) scheme. However, the DPC scheme is quite difficult to be implemented in the real‐time scenario as the computational complexity is very high and the process cannot be accomplished within the duration of few coherence periods. In this paper, we have adopted a newly developed binary spider monkey optimization (binary SMO) algorithm for the joint user and antenna scheduling (JUAS) problem to maximize the achievable system sum‐rate performance. It has been shown that JUAS with binary SMO achieves nearly 99% of system throughput achieved by the extensive search algorithm (ESA) using DPC. Also it is compared with binary flower pollination algorithm (binary FPA) to check which of the two gives better result. It is observed that the binary SMO in JUAS achieves a globally optimal solution quite rapidly, to remain well within the modern‐day packet data communication interval. The proposed binary SMO shows low computational complexity and computation time as compared to ESA (i.e., DPC). Also when it is compared with binary FPA, it shows quite a significant improvement in system throughput. Moreover, the effectiveness of binary SMO in the MU‐MIMO broadcasting scenario is verified through extensive simulation results.

Meta‐heuristic optimization techniques for scheduling in multiple‐input multiple‐output multiple‐access channel system

“…35 The significant observation is that compared with the optimal technique, the near-optimal throughput may be achieved with far less computational complexity. In Mohanty et al, 36 a MU-MIMO system, the spider monkey optimization (SMO) is utilized for the joint user and antenna scheduling purpose. The authors attempt to optimize the achievable sum-rate capacity with as little computational complexity as possible.…”

Binary Flower Pollination Algorithm Based User Scheduling for Multiuser MIMO Systems

“…It is also not possible to search such high dimensional search space in the span of a usual scheduling interval (few coherence time periods). Recently meta-heuristic soft computing techniques are implemented for various multi-antenna system models [24][25][26]. This motivates us to explore the possibilities of implementing an evolutionary algorithm to achieve this task.…”