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

• Main Authors: Karel Charles-Darby, Roberto Carrasco-Alvarez, R. Parra-Michel
• Format: Article
• Language: English
• Published: MDPI AG 2019-11-01
• Series: Electronics
• Subjects: basis expansion modeling (bem); doubly selective channels; maximum a posteriori probability (map); maximum likelihood sequence estimation (mlse); single-carrier transmission
• Online Access: https://www.mdpi.com/2079-9292/8/11/1333

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.