Abstract:

In this article, a multiuser (MU) multiinput multioutput (MIMO) system is considered, which is essential to support a huge number of subscribers without consuming extra bandwidth or power. Dirty paper coding (DPC) for MU MIMO channel achieves the peak sum-rate for the MU multiple antenna system at the cost of high computational complexity. Both user and antenna scheduling with a population based meta-heuristic algorithm, i.e. binary flower pollination algorithm (binary FPA) has been demonstrated in this article to achieve system sum-rate comparable to DPC with very less computational complexity and time complexity. Moreover, binary FPA shows a significant improvement in system throughput/sum-rate performance as compared to other population based meta-heuristic algorithms like binary bat algorithm (binary BA) and binary genetic algorithm (binary GA). Furthermore, the proposed binary FPA algorithm successfully achieves higher system sum-rate as compared to random search scheme and different existing suboptimal scheduling algorithms from literature as well. The binary FPA has also better convergence rate and searching ability than both binary BA and binary GA techniques. The percentage deviation achieved by the proposed binary FPA algorithm is quite less than that of binary BA, binary GA, random search method, and existing suboptimal scheduling algorithms from the literature. The efficiency of binary FPA in all these fronts is verified using exhaustive simulation studies.

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