提升NOMA系统性能的多决策SIC接收器

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本文档标题为"Multiple Decision Aided Successive Interference Cancellation (MD-SIC)接收器在非正交多址(NOMA)系统中的应用",发表于2017年8月的IEEE Wireless Communications Letters第6卷第4期。NOMA作为5G通信系统的关键技术之一，因其能高效地支持大规模连接，引起了广泛关注。传统NOMA系统中， Successive Interference Cancellation (SIC) 是一种常见的用户检测策略，它通过逐次解调并移除其他用户的信号来实现多个用户的通信。然而，传统的SIC方法存在一个主要问题，即错误在解调过程中会逐层累积，导致性能下降。为了克服这个挑战，本文提出了一种创新的MD-SIC策略。与传统SIC中每个用户仅选择一个候选解码码字不同，MD-SIC引入了多个候选码字，以此减少误差传播的影响。这样做的目的是通过引入更多可能的选择来提高检测的鲁棒性，同时试图在性能提升与计算复杂度之间找到一个平衡。文章设计了一个用户特定的阈值，用来控制每个用户候选集的大小，这有助于控制算法的复杂性。通过模拟实验，结果显示MD-SIC算法在保持相对较低额外计算负担的前提下，显著优于传统的SIC接收器，显示出在实际通信系统中具有显著的优势。因此，本研究对NOMA系统的接收器设计提出了一个重要改进，对于提升多用户通信系统的性能、降低错误传播风险以及优化资源利用具有重要的理论和实践意义。在未来无线通信网络的设计和优化中，MD-SIC算法有望成为一种关键的技术手段。

498 IEEE WIRELESS COMMUNICATIONS LETTERS, VOL. 6, NO. 4, AUGUST 2017

Multiple Decision Aided Successive Interference

Cancellation Receiver for NOMA Systems

Binjian Ling, Chao Dong, Jincheng Dai, and Jiaru Lin

Abstract—Non-orthogonal multiple access (NOMA) is one of

the critical technologies in ﬁfth generation systems. Successive

interference cancellation (SIC) is a typical solution of multiple

users detection in NOMA systems. However, conventional SIC

suffers from error propagation. To alleviate this problem, in this

letter, a multiple decision SIC (MD-SIC) strategy is introduced.

Instead of choosing one codeword for each user in traditional SIC

detection, the proposed algorithm introduces multiple codewords

as the candidates to combat the error propagation. Furthermore,

a threshold is designed to control the size of candidate set for each

user. It helps the MD-SIC to achieve a better tradeoff between

performance and complexity. The simulation results indicate that

the MD-SIC algorithm obviously outperforms the conventional

SIC with a little additional computational complexity.

Index Terms—NOMA systems, successive interference cancel-

lation, multiple decision, error propagation mitigation.

I. INTRODUCTION

ON-ORTHOGONAL multiple access (NOMA) acts as a

promising technology to meet the requirement of increas-

ingly higher capacity in the ﬁfth generation (5G) mobile

communication systems. Recently, sparse code multiple access

(SCMA) [1] and pattern division multiple access (PDMA) [2]

have become two typical code-domain non-orthogonal tech-

nologies. In both of the two technologies, each user’s bit

stream is directly mapped onto a sparse codeword and

multiple users share the same orthogonal physical resource

elements (PREs). This kind of overloading transmission effec-

tively supports the demand of massive connections in the

5G systems. For PDMA, the number of users superim-

posed on the same PRE may be different [3], which differs

from SCMA.

In the receiver of NOMA systems, the maximum likeli-

hood (ML) detection provides the lower bound of multiuser

detection performance by traversing all the possible signal

combinations. Nevertheless, the computational complexity of

ML algorithm increases exponentially with the number of

access users and modulation order. Therefore, it is difﬁcult to

be applied in practical systems. Successive interference can-

cellation (SIC) is the most well-known detection technology in

Manuscript received April 14, 2017; revised May 20, 2017; accepted

May 20, 2017. Date of publication May 25, 2017; date of current version

August 21, 2017. This work was supported in part by the NSFC under Grant

61601047 and Grant 61671080, and in part by the BUPT-SICE Excellent

Graduate Students Innovation Fund. The associate editor coordinating the

review of this paper and approving it for publication was R. C. de Lamare.

(Corresponding author: Binjian Ling.)

The authors are with the Key Laboratory of Universal Wireless

Communications, Ministry of Education, Beijing University of

Posts and Telecommunications, Beijing 100876, China (e-mail:

lingbinjian@bupt.edu.cn; dongchao@bupt.edu.cn; daijincheng@bupt.edu.cn;

jrlin@bupt.edu.cn).

Digital Object Identiﬁer 10.1109/LWC.2017.2708117

NOMA systems. Theoretically, the use of SIC provides capa-

bility to approach the boundary of MAC-RR [4]. Furthermore,

the computational complexity of SIC is much lower than that

of ML. In spite of all these advantages above, in the prac-

tical communication systems, it suffers from a performance

loss due to the error propagation [2]. Especially, when there

exist correlations among user access channels, the performance

of SIC receiver will further degrade. The mitigation of error

propagation is investigated in [5]–[10].

In this letter, to alleviate the above error propagation

problem, a multiple decision successive interference cancella-

tion (MD-SIC) algorithm is proposed. Standard SIC detection

is regarded as a process of searching the single path greed-

ily in the decision tree. Hence, there is no chance to correct

the inaccurate decisions of previous users. While in MD-SIC,

multi-branch expansion is employed at the instantaneously

detecting node. Conventional SIC detection is adopted for

the subsequent users’ signal detection. By doing so, more

points in the decision tree are considered and the error

propagation is obviously mitigated. It is worth noting that,

unlike MF-SIC in [5], the proposed strategy replaces MMSE

algorithm with a local ML (local_ML) function for better

performance and lower complexity. Furthermore, a predeﬁned

threshold is proposed to prune the unnecessary branches,

which keeps a better balance between performance and com-

plexity. Simulation results indicate that the performance of

MD-SIC algorithm approaches the ML solution with compa-

rable complexity to the standard SIC receiver.

The organization of this letter is as follows. Section II

describes the notation conventions, and NOMA system model.

Section III is committed to introducing the MD-SIC algorithm.

Section IV performances the evaluation results. Conclusions

are given in Section V.

II. N

OTATIONS AND SYSTEM MODEL

A. Notation Conventions

In this letter, calligraphic characters such as

X is used to

denote sets. We write lowercase letters (e.g., x) to denote

scalars. Let the notation x denote a vector and x

to denote

the i-th element in x. The set of binary, real and complex

numbers are denoted by B, R and C, respectively. The bold

letters, such as X, denote matrices, X

is the i-th row of

matrix X, and X

i,j

is the element at the i-th row and the

j-th column of matrix X. For a diagonal matrix diag(x),

its i-th diagonal element is x

. The notations X

and x

stand for the transpose of matrix X and vector x, respectively.

Throughout this letter, the function log(·) means “logarithm

to base 2”, and the function ln(·) stands for the “logarithm

to base e”.

2162-2345

 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

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