Open AccessPerformance Measurement and Optimization of Relays Used for 5G Ultra Reliable Low Latency Communication Network
Author(s) -
Mr. Saraju Prasad Padhy*,
Mrs. Madhusmita Panda,
Srinivas Sethi,
Aruna Tripathy
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e6899.018520
Subject(s) - relay , block error rate , computer science , decoding methods , throughput , node (physics) , particle swarm optimization , block (permutation group theory) , coding (social sciences) , optimization problem , linear network coding , algorithm , power (physics) , electronic engineering , real time computing , telecommunications , computer network , mathematics , engineering , wireless , telecommunications link , statistics , physics , geometry , structural engineering , quantum mechanics , network packet
The objective of this paper is to analyse and optimize the performance parameters of Relay nodes used in the finite block length (FBL) regime. A relaying system with a single Decode and Forward (DF) Relay is used for this purpose. Here using FBL, the performance parameters like coding rate, decoding error probability etc are obtained for different scenarios like without relay, with relay and using cooperative relaying. Effects of SNR and code Block length on performance parameters are analyzed. To enhance the performance of the Relay in URLLC scenario, power distribution between source and Relay node is optimized using evolutionary algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Infeasibility Driven Evolutionary Algorithm (IDEA). Low error probability and high throughput at the desired block length and power were the optimization goals. After using both the algorithms, the optimized Relay has shown improvement in performances like throughput (coding rate) and decoding error probability. It is also observed that IDEA optimization approach is found to be more efficient than MOPSO to provide optimum design parameters.