Optimization of iterative PIC-MMSE based
detection with symbol mapping
Meixiang Zhang and Chunxiao Li
College of Information Engineering
Yangzhou University, Yangzhou, China 225127
Email: maehyang@foxmail.com, licx@yzu.edu.cn
Saleem Ahmed
Dawood University of
Engineering and Technology
Karachi, Pakistan 74800
Email: saleem3714@gmail.com
Sooyoung Kim
Chonbuk National University
Jeonju, Korea 561-756
Email: sookim@jbnu.ac.kr
Abstract—Recently, the iterative detection and decoding tech-
nique based on parallel interference cancellation with minimum
mean square error (PIC-MMSE) has received considerable
attention. To improve the performance, the detector usually
adopts a self-iteration which iteratively estimate the soft bit
information (SBI). This paper proposes two main idea to improve
the performance as well as to reduce the complexity of the PIC-
MMSE based MIMO detector. In order to reduce the complexity,
we map PIC-MMSE filtered symbol to a specific region so that the
detector does not require any search process to find the minima.
In addition, we propose an optimization technique to increase
the reliability of the soft symbols. Simulation results show that
the complexity of the proposed method is reduced to linear-order
without performance degradation, and the proposed optimization
method can efficiently improve the performance with reasonable
complexity.
Index Terms—symbol mapping, iterative detection and de-
coding, self-iteration, PIC-MMSE, MIMO detection, soft bit
estimation.
I. INTRODUCTION
The multi-input multi-output (MIMO) scheme is one of the
essential techniques for modern wireless systems. At the same
time, in order to combat harsh channel condition, forward error
correction (FEC) schemes with iterative decoding algorithms
are generally used, resulting in coded MIMO systems with
soft detection. The design of efficient MIMO detector pro-
ducing accurate soft information is a challenging task in the
coded MIMO systems. A detector maximize the a posteriori
probability (MAP) achieves an optimal performance, while
its computational complexity increases exponentially with the
number of antennas and the number of bits per symbol. A
number of sub-optimal algorithms were proposed to reduce
the complexity, but their complexities are still too high for
real applications [1]-[5].
The parallel interference cancellation with minimum mean
square error (PIC-MMSE) based MIMO detection has received
considerable attention recently, due to its good performance-
complexity tradeoff for coded MIMO systems [6]-[9]. The
core idea of the PIC-MMSE detector is to compute estimates
of the transmitted symbols based on the a priori log-likelihood
This research was supported by the National Natural Science Foundation of
China (Grant No. 61601403), and Basic Science Research Program through
the National Research Foundation of Korea(NRF) funded by the Ministry of
Science, ICT & Future Planning(NRF-2014R1A1A2055489).
ratio (LLR) from the channel decoder. The estimated symbols
are then utilized to cancel the interference in the received
signal vector. Afterwards, the soft bit information (SBI) is
calculated based on MAP algorithm. The performance of
the PIC-MMSE detector can be enhance by using iterative
detection and decoding (IDD), with a self-iteration inside the
detector. The PIC-MMSE based MIMO detection reduces the
complexity of the symbol detection to linear order, while its
complexity of SBI estimation from a symbol is still in an
exponential order.
In this paper, we propose an efficient PIC-MMSE based
MIMO detection, by reducing the complexity of the soft
MIMO detection to a linear order. We adopt an efficient SBI
estimation method using a symbol mapping technique [11],
and tailor it for the PIC-MMSE filtered symbols after normal-
ization. With this method, we can reduce the computational
complexity of the SBI estimation to nearly linear-order without
degrading the bit error rate (BER) performance. In addition,
we propose an efficient optimization method to improve the
performance, based on the reliability of the minima.
The remainder of this paper is organized as follows. Section
II reviews a MIMO system model with IDD, and describe
the operational principles of the PIC-MMSE based MIMO
detection. In Section III, the proposed PIC-MMSE detector
with a symbol mapping based detection is explained, and
the optimization technique is additionally introduced. Section
IV demonstrates the bit error rate (BER) performance of the
proposed methods compared with the conventional scheme and
compares the computational complexity of them. Finally, we
draw conclusions in Section V.
II. PIC-MMSE BASED DETECTION FOR IDD
A. System model
Figure 1 shows the block diagram for an N
t
× N
r
MIMO
system with IDD. At the transmitter, the bit information
vector u is encoded to produce codeword c. Then N
t
· K
codewords are interleaved and modulated successively before
they are mapped to the N
t
transmitted antennas, where K
is the number of bits per transmitted symbol. The inter-
leaved bits x = [x
1,1
, · · · , x
1,K
, x
2,1
, · · · , x
m,k
, · · · , x
N
t
,K
]
are divided and modulated to transmitted symbol vector s =
[s
1
, s
2
, · · · , s
m
, · · · , s
N
t
]
T
, where x
m,k
represents the kth bit