Particle swarm optimization of the spectral and energy efficiency of an SCMA‐based heterogeneous cellular network

Abstract

Background: The effect of stochastic small base station (SBS) deployment on the energy efficiency (EE) and spectral efficiency (SE) of sparse code multiple access (SCMA)-based heterogeneous cellular networks (HCNs) is still mostly unknown.Aim: This research study seeks to provide insight into the interaction between SE and EE in SBS sleep-mode enabled SCMA-based HCNs.Methodology: A model that characterizes the energy-spectral-efficiency (ESE) of a two-tier SBS sleep-mode enabled SCMA-based HCN was derived. A multiobjective optimization problem was formulated to maximize the SE and EE of the SCMA-based HCN simultaneously. The multiobjective optimization problem was solved using a proposed weighted sum modified particle swarm optimization algorithm (PSO). A comparison was made between the performance of the proposed weighted sum modified PSO algorithm and the genetic algorithm (GA) and the case where the SCMA-based HCN is unoptimized. Results: The Pareto-optimal front generated showed a simultaneous maximization of the SE and EE of the SCMA-based HCN at high traffic levels and a convex front that allows network operators to select the SE-EE tradeoff at low traffic levels flexibly. The proposed PSO algorithm offers a higher SBS density, and a higher SBS transmit power at high traffic levels than at low traffic levels. The unoptimized SCMA-based HCN achieves an 80% lower SE and a 51% lower EE than the proposed PSO optimized SCMA-based HCN. The optimum SE and EE achieved by the SCMA-based HCN using the proposed PSO algorithm or the GA are comparable, but the proposed PSO uses a 51.85% lower SBS density and a 35.96% lower SBS transmit power to achieve the optimal SE and EE at moderate traffic levels. Conclusion:In sleep-mode enabled SCMA-based HCNs, network engineers have to decide the balance of SBS density and SBS transmit power that helps achieve the desired SE and EE.

A Novel Epidemic-Based Video Diffusion Strategy Using Awareness of Sociality and Mobility in Wireless Networks

“…The event that u h accepts the only video pushed by u k does not happen, namely FL hk = 1, vs k h = vs k→h = 1 happens with a low probability. The average success rate of acceptance of u h can see the formula (6).…”

“…The fast-changing communication technologies, such as the deployment of 5G and the development of 6G, greatly promote network bandwidth and data delivery quality for the mobile Internet, which effectively supports online services with high requirements of bandwidth and delivery performance (e.g., video-on-demand and video living) [1][2][3][4]. The video services rely on rich viewing content to attract a large number of users, which generates huge traffic demand and consumes a mass of network bandwidth [5][6][7][8]. Currently, there is a deep integration between video services and social networks.…”