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Sphere Decoding Complexity Reduction using an Adaptive SD-OSIC
Algorithm
Bora Kim, Sangmi Moon, Saransh Malik, Cheolhong Kim and Intae Hwang
Department of Electronics and Computer Engineering, Chonnam National University,
300 Yongbong-Dong, Buk-Gu, Gwangju, Republic of Korea
Keywords: Link Adaptation, MIMO, OSIC, SNR, Sphere Decoding.
Abstract: Sphere decoding is a technique able to achieve the optimal performance of the maximum likelihood
decoder, but its high and variable complexity can make the practical implementation infeasible. In this
paper, we present an adaptive system, called adaptive SD-OSIC, as a way of reducing the decoding
complexity while maintaining the error performance of conventional sphere decoding.
1 INTRODUCTION
OPTIMAL maximum likelihood (ML) decoding
measures the distance from the received vector to
all possible codewords in the lattice, but if we use a
multiple-input multiple-output (MIMO) system with
transmit antennas, and modulation of
2
constellation points, where is the number of bits
per symbol, the number of possibilities for vector
that should be tested becomes 2
. In 1999,
Viterbo and Boutros (Viterbos and Boutros, 1999)
proposed a universal lattice decoding technique, now
known as sphere decoding (SD), which achieves the
error performance of ML, but simplifies the search
by restricting it to codewords that lie inside a sphere
centered at the received signal vector. SD algorithm
is less complex than the conventional ML, but the
number of operations that must be performed varies
with the SNR and channel conditions; therefore,
suboptimal decoding techniques, such as zero
forcing (ZF), minimum mean-square error (MMSE),
and ordered successive interference cancelation
(OSIC) are usually preferred as they are easier to
implement in hardware.
Among the recent attempts to reduce SD
complexity are hybrid SD-ZF (Lee and Kim, 2006),
K-best (Viterbos and Boutros, 1999) and fixed SD
(FSD) (Guo and Nilsson, 2006); (Barbero and
Thompson); the last two techniques achieve a
constant number of iterations independent of the
SNR or channel conditions, but exhibit a tradeoff
between the bit error rate (BER) performance and
computational cost; while the former one proposes
reducing the search operations performed by SD by
decoding the symbols with high SNR using ZF.
In this paper, we propose to reduce the number
of iterations needed by conventional SD and
improve the concept presented in (Lee and Kim,
2006) by combining SD, OSIC, and the principle of
link adaptation. The resulting system achieves a very
low, quasi-constant complexity over the entire SNR
range, exhibits better error performance than SD and
OSIC at a low SNR, and makes a minimum sacrifice
of BER at a high SNR.
This paper is divided as follows: Sections II and
III explain the SD algorithm and the Adaptive SD-
OSIC system, respectively; Section IV presents and
discusses the simulation results; and, in Section V,
we present our conclusions.
Figure 1: Graphic representation of the SD concept.
2 SD ALGORITHM
In a MIMO system with
transmit antennas and
75
Kim B., Moon S., Malik S., Kim C. and Hwang I..
Sphere Decoding Complexity Reduction using an Adaptive SD-OSIC Algorithm.
DOI: 10.5220/0004027200750080
In Proceedings of the International Conference on Signal Processing and Multimedia Applications and Wireless Information Networks and Systems
(SIGMAP-2012), pages 75-80
ISBN: 978-989-8565-25-9
Copyright
c
2012 SCITEPRESS (Science and Technology Publications, Lda.)