Experimental design of adaptive algorithms to reduce SER in M-ary QAM System (International Journal of Engineering and Computer Science, 2018)
This paper presents an experimental design of adaptive algorithms to investigation of Symbol error rate for adaptive training algorithms without involving with any modified or design algorithms, two conventional adaptive equalizer training methods, the least mean squares (LMS) and recursive least squares (RLS), are implemented in a Quadrature amplitude modulation over sampled received sequence and their performances are compared in different parameters like symbol size, step size and rotation. The  algorithms  were  evaluated  using  convergence SER at  SNR  of  20 dB  over  different  number  of  iterations  to  determine  the convergence rate and constellation diagra