Complexity Reduction of MLSE and MAP Equalizers Using Modified Prolate Basis Expansion

Karel Charles-Darby,Roberto Carrasco-Alvarez,R Parra-Michel

doi:10.3390/electronics8111333

Abstract

Maximum likelihood sequence estimation (MLSE) and maximum a posteriori probability (MAP) equalizers are optimum receivers for dealing with intersymbol interference (ISI) in time-dispersive channels. However, their high complexity and latency limit their widespread implementation; therefore, research into reducing their complexity is an open topic. This paper proposes a novel modification to reduce the computational complexity of the aforementioned algorithms, which exploits the representation of the communication channels in a time-delay-domain basis expansion model (BEM). It is shown that an appropriate basis is a set of modified prolate functions, in which the transmitter and receiver filters are considered in the kernel construction. Simulation results show that a reduction in sums and multiplications on the order of 55% can be obtained, maintaining the same bit error rate performance as in the traditional implementation.

Highlights

Reflection, refraction, and diffraction are propagation phenomena that cause many delayed replicas of the transmitted signal to reach the receiver
This paper presents a modification of Maximum likelihood sequence estimation (MLSE) and maximum a posteriori probability (MAP) algorithms using a basis expansion model, which allows translating part of the computational complexity into memory storage
The simulation results confirm that the performance of the orthogonal equalizers is quite similar to that of the MLSE

Summary

Introduction

Reflection, refraction, and diffraction are propagation phenomena that cause many delayed replicas of the transmitted signal to reach the receiver. If the maximum delay of these replicas τmax is close to or greater than the symbol period T, each received symbol possesses energy from its neighbors. This impairment is known as intersymbol interference (ISI), and it greatly degrades system performance. OFDM has two major drawbacks: high sensitivity to Doppler spread, dependent on the system’s mobility, and a high peak-to-average power ratio (PAPR), proportional to the length of the Fourier transform. To avoid excessive PAPR while complexity equalization remains low in the frequency domain, the discrete-Fourier-transform (DFT)-Spread OFDM has been employed

Methods

Results

Conclusion