Multiple Delay Estimation Using Genetic Algorithm-Based MCMC in Non-Orthogonal Random Access

In machine-type communication (MTC), since multiple active devices are located randomly in a cell, the arrival time of multiple signals can be different. A priori information on the arrival time of multiple signals is helpful to estimate more specific parameters such as the number of signals, which is essential to employ the successive interference cancellation (SIC) to improve throughput of a non-orthogonal random access (NORA) system. In this letter, we propose an approach to estimate the round-trip delay (RTD) of multiple signals based on Markov chain Monte Carlo (MCMC) and Genetic Algorithm (GA). Simulation results show our proposed GA-based MCMC method can achieve high performance with low complexity.