| Autor: |
Akpari, Evans Wilson, Nunoo, Solomon, Deynu, Faith Kwaku, Apprey, Michael Wellington |
| Předmět: |
|
| Zdroj: |
Journal of Microwaves, Optoelectronics & Electromagnetic Applications; Sep2022, Vol. 21 Issue 3, p453-480, 28p |
| Abstrakt: |
Broadband Power Line Communication (BB-PLC) technology enables data transmission for smart grid applications. Nevertheless, channel equalizers are required in the receiver to estimate and compensate for the nonlinear time-variant impulse response and noise interference effects introduced by the BB-PLC channel. In this paper, we append the Particle Swarm Optimization (PSO) algorithm and its proposed improved version to the commonly used Least-Square (LS) and Linear Minimum Mean Square Error (LMMSE) algorithms to advance four new blocktype pilot-aided hybrid channel estimation algorithms for lowvoltage Orthogonal Frequency Division Multiplexing (OFDM)- based BB-PLC systems. Extensive numerical simulation results for four different M-QAM formats (M = 8, 16, 32, 64) show that the proposed algorithms significantly improve the performance of the traditional LS and LMMSE estimators, at least for the parameters of the BB-PLC system studied in this work. In addition, the computational load complexity of the PSO-inspired LMMSE algorithm is lower compared to the conventional LMMSE estimator. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
