Performance analysis of cooperative small cell systems under correlated Rician/Gamma fading channels. Issue 1 (1st February 2018)

• Record Type: Journal Article
• Authors: Li, Xingwang; Li, Jingjing; Li, Lihua; Du, Liutong; Jin, Jin; Zhang, Di
• Is Part Of: IET signal processing. Volume 12:Issue 1(2018)
• Page Start: 64
• Page End: 73
• Publication Date: 2018-02-01
• Subjects: Rician channels -- fading channels -- radio networks -- Monte Carlo methods -- radio receivers -- telecommunication traffic; cooperative small cell systems -- correlated Rician/Gamma fading channels -- SCN -- data traffic -- wireless communications -- base stations -- BS -- interference -- cooperative transmission mechanism -- zero forcing receivers -- outage probability -- symbol error rate -- achievable sum rate -- Rician factors -- correlation coefficients -- Monte‐Carlo simulation; Signal processing -- Periodicals; 621.3822
• DOI: 10.1049/iet-spr.2017.0078
• Languages: English
• ISSNs: 1751-9675

Abstract

Abstract : Small cell networks (SCNs) have emerged as promising technologies to meet the data traffic demands for the future wireless communications. However, the benefits of SCNs are limited to their hard handovers between base stations (BSs). In addition, the interference is another challenging issue. To solve this problem, this study employs a cooperative transmission mechanism focusing on correlated Rician/Gamma fading channels with zero‐forcing receivers. The analytical expressions for the achievable sum rate, symbol error rate and outage probability are derived, which are applicable to arbitrary Rician factors, correlation coefficients, the number of antennas, and remain tight across entire signal‐to‐noise ratios (SNRs). Asymptotic analyses at the high and low SNR regimes are carried out in order to further reveal the insights of the model parameters on the system performance. Monte‐Carlo simulation results validate the correctness of their derivations. Numerical results indicate that the theoretical expressions provide sufficiently accurate approximation to simulated results.