A near maximum a posteriori (MAP)-optimal soft detector that outputs a posteriori probabilities (APP's) for multiple-input multiple-output (MIMO) systems in flat fading channels is proposed. This is referred to as 'reduced state maximum a posteriori (RSMAP)' algorithm. This detection algorithm is based on BCJR algorithm and also uses ideas from reduced state sequence estimation (RSSE) and set partitioning. This algorithm is shown to be near optimal and the computational complexity to implement it is estimated. Finally we also show that applying the well known max-log approximation on this algorithm results in nearly same performance at much lower complexity. © 2012 IEEE.

R. David Koilpillai

Department of Electrical Engineering

A-POSTERIORI PROBABILITIES

BCJR ALGORITHM

Detection algorithm

FLAT-FADING CHANNELS

LOWER COMPLEXITY

Maximum a posteriori

MIMO DETECTION

MULTIPLE-INPUT-MULTIPLE-OUTPUT SYSTEMS

REDUCED-STATE

REDUCED-STATE SEQUENCE ESTIMATION

SET PARTITIONING

SOFT DECISION

SOFT DETECTOR

Fading channels

MIMO systems

Optimization

signal processing

Approximation algorithms

IIT Madras is a public technical and research university located in Chennai, Tamil Nadu. Founded in 1959, it is recognised as an Institute of National Importance.

IIT Madras has been ranked as the top engineering institute in India for four years in a row by the National Institutional Ranking Framework of the MHRD

It currently offers undergraduate, postgraduate and research degrees across 16 disciplines in Engineering, Sciences, Humanities and Management. About 596 faculty belonging to science and engineering departments and centres of the Institute are engaged in teaching, research and industrial consultancy.

IIT Madras

Set-partitioning based forward/backward soft decision algorithms for MIMO detection

2012 International Conference on Signal Processing and Communications, SPCOM 2012

A reduced complexity soft-output joint equalization scheme is proposed for MIMO-ISI systems employing Higher Order Modulation (HOM). Multi-dimensional set partitioning proposed by Zhang et.al. [1] is applied to form a reduced-state trellis or the subset trellis. The Max-Log-MAP algorithm is modified to operate on the subset trellis in order to generate soft information at reduced complexity. The backward recursion can often be avoided since the forward recursion of the Max-LogMAP algorithm is capable of providing reliable soft information when some fixed decision delay is introduced. This idea is leveraged in the equalization scheme proposed in this paper. It generates soft information using only the forward recursion of the Max-Log-MAP algorithm and is referred to as the Forward-Only algorithm. A key requirement of reduced-state equalization is the ability to decide winners of parallel transitions using low-complexity slicing operations, which is accomplished via a novel flexible-complexity algorithm, viz., Reduced-State Tree Detection. Due to set partitioning, soft decision failure can occur in the forward-only algorithm and in such an event, a general approach to regenerate soft information using delayed decision feedback is proposed. The low complexity and memory requirements of the forward-only algorithm makes it attractive for MIMO-ISI equalization. © 2014 IEEE.

2014 20th National Conference on Communications, NCC 2014

Reduced-state soft-output equalization for MIMO-ISI systems employing HOM

A multi-dimensional set-partitioning scheme is proposed for joint reduced-state sequence detection (JRSSD) of vector sequences corrupted by intersymbol interference (ISI) and additive white Gaussian noise (AWGN). The existing multi-dimensional set-partitioning schemes result in complexity exponential in the dimensionality of the vectors in the vector sequence. The proposed set-partitioning scheme allows the construction of reduced-state trellises with very few states even when the vectors are of high dimensionality. One of the key requirements of the JRSSD algorithm is an efficient algorithm for spatial multi-symbol detection, for which we propose the reduced-state tree (RST) detection algorithm. In addition to performance improvement, the inclusion of RST algorithm for spatial multi-symbol detection provides a common framework for designing receivers for both flat-fading and frequency-selective fading MIMO channels. © 2014 IEEE.

IEEE Communications Letters

Generalized reduced-state vector sequence detection

Medical History

The University of Virginia Claude Moore Health Science Library Online Collections, available online at  http://www.hsl.virginia.edu/historical/exhibits2.cfm

IEEE Transactions on Wireless Communications

Low-complexity adaptive tree search algorithm for MIMO detection

Fixing the Complexity of the Sphere Decoder for MIMO Detection

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

A Low-Complexity Soft-MIMO Detector Based on the Fixed-Complexity Sphere Decoder

Coset detection in MIMO systems based on spatial multiplexing

Journal	2012 International Conference on Signal Processing and Communications, SPCOM 2012
Open Access	No