Computationally Efficient Scheduling Schemes for Multiple Antenna Systems Using Evolutionary Algorithms and Swarm Optimization

Pattanayak, Prabina; Kumar, Pawan

doi:10.1002/9781119574293.ch5

Cited by 11 publications

(2 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By the number of times the utility function is calculated, the computational complexity is measured. The total number of complex additions and multiplications (CAM) accomplished by the various algorithms is regarded as a measure of computational complexity which has been discussed in [25,40]. It may be seen from Eq.…”

Section: Complexity Analysismentioning

confidence: 99%

Binary Flower Pollination Algorithm Based User Scheduling for Multiuser MIMO Systems

2021

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

Section: Complexity Analysismentioning

confidence: 99%

Binary Flower Pollination Algorithm Based User Scheduling for Multiuser MIMO Systems

2021

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

“…This is beyond a few coherence times of the system. Therefore, in the past, various soft computing techniques have been used for different MU multiple‐antenna system models 5,41–43 . This motivated us to search for a competent soft computing technique which can be evaluated for the present MU‐MIMO system model to search the optimum result swiftly.…”

Section: Introductionmentioning

confidence: 99%

MIMO broadcast scheduling using binary spider monkey optimization algorithm

Mohanty

Pattanayak

Nandi

et al. 2021

Int J Communication

Self Cite

View full text Add to dashboard Cite

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.

show abstract