Xubin Lin

Bio: Xubin Lin is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Decoding methods & Noise. The author has an hindex of 3, co-authored 3 publications receiving 18 citations.

Clipping Noise-Aided Message Passing Algorithm for SCMA-OFDM System

Abstract: Sparse code multiple access combined with orthogonal frequency division multiplexing (SCMA-OFDM) is a promising wireless air-interface technology for fifth generation (5G) networks to support massive connections. The existing problem for SCMA-OFDM system is that the peak-to-average power ratio (PAPR) is unbearable high. The clipping method is often adopted to reduce the PAPR. However, the clipping brings extra noise to the SCMA-OFDM system. Due to the conventional message passing algorithm (C-MPA) didn’t consider the clipping noise, it will cause the C-MPA decoding to be inaccurate and degrade the bit error rate performance. To tackle this issue, a novel clipping noise-aided MPA scheme, named CNA-MPA, which take both the additive white Gaussian noise (AWGN) and the clipping noise into consideration for decoding accurately is proposed. Simulation results show that the analysis of the clipping noise is accurate and the proposed CNA-MPA scheme leveraging both the AWGN and clipping noise can handle the phenomenon of the performance deterioration occurred in the C-MPA scheme at high Eb/N0 regime.

Iterative Clipping Noise Elimination of Clipped and Filtered SCMA-OFDM System

Abstract: Similar to conventional orthogonal frequency division multiplexing (OFDM) signal, the signals of sparse code multiple access combine with orthogonal frequency division multiplexing (SCMA-OFDM) existing the problem that its peak-to-average power ratio (PAPR) is unbearable high. In this paper, the clipping method is adopted to reduce the PAPR of the SCMA-OFDM signal. However, the clipping process brings extra noise to the SCMA-OFDM signal while the clipping noise is not taken into account in the message passing algorithm (MPA), which makes the MPA detection inaccurate and leads to a phenomenon that the decoding performance declines sharply with the increasing of ${{\text {E}}_{\text {b}}}{{/}}{{\text {N}}_{{0}}}$ . Moreover, due to the distortion of SCMA-OFDM signals caused by clipping process, the system bit error rate (BER) performance degrades obviously. To tackle the issues above, we analyze the random characteristics of the clipping noise for the MPA detection scheme. Then, an iterative clipping noise elimination scheme is proposed to restore the BER performance of clipped SCMA-OFDM system. Simulation results show that our method can remove the phenomenon that the BER performance declines sharply at the high ${{\text {E}}_{\text {b}}}{{/}}{{\text {N}}_{{0}}}$ region and the proposed iterative clipping noise elimination scheme restores the BER performance significantly.

Method for lowering decoding complexity of sparse code multiple access (SCMA) system

Abstract: The invention belongs to the technical field of wireless communication, in particular to a method for lowering the decoding complexity of a sparse code multiple access (SCMA) system. The decoding complexity of the SCMA system can be lowered greatly by dynamically reducing the number of edges involved in message update in a factor graph during a message iterative updating process. Through selectionof the number of different edges for which message update is stopped, a compromise is made between SCMA multi-user detection complexity and bit error rate (BER) performance. Thus, the method can alsoadaptively meet the communication quality requirements of 5G under different scenarios.

Multidimensional Constellations for Uplink SCMA Systems—A Comparative Study

Abstract: Sparse code multiple access (SCMA) is a class of non-orthogonal multiple access (NOMA) that is proposed to support uplink machine-type communication services. In an SCMA system, designing multidimensional constellation plays an important role in the performance of the system. Since the behavior of multidimensional constellations highly depends on the type of the channel, it is crucial to employ a constellation that is suitable for a certain application. In this paper, we first highlight and review the key performance indicators (KPIs) of multidimensional constellations that should be considered in their design process for various channel scenarios. We then provide a survey on the known multidimensional constellations in the context of SCMA systems with their design criteria. The performance of some of those constellations are evaluated for uncoded, high-rate, and low-rate LTE turbo-coded SCMA systems under different channel conditions through extensive simulations. All turbo-coded comparisons are performed for bit-interleaved coded modulation, with a concatenated detection and decoding scheme. Simulation results confirm that multidimensional constellations that satisfy KPIs of a certain channel scenario outperform others. Moreover, the bit error rate performance of uncoded systems, and the performance of the coded systems are coupled to their bit-labeling. The performance of the systems also remarkably depends on the behavior of the multiuser detector at different signal-to-noise ratio regions.

Multidimensional Constellations for Uplink SCMA Systems --- A Comparative Study

Abstract: Sparse code multiple access (SCMA) is a class of non-orthogonal multiple access (NOMA) that is proposed to support uplink machine-type communication services. In an SCMA system, designing multidimensional constellation plays an important role in the performance of the system. Since the behaviour of multidimensional constellations highly depends on the type of the channel, it is crucial to employ a constellation that is suitable for a certain application. In this paper, we first highlight and review the key performance indicators (KPIs) of multidimensional constellations that should be considered in their design process for various channel scenarios. We then provide a survey on the known multidimensional constellations in the context of SCMA systems with their design criteria. The performance of some of those constellations are evaluated for uncoded, high-rate, and low-rate LTE turbo-coded SCMA systems under different channel conditions through extensive simulations. All turbo-coded comparisons are performed for bit-interleaved coded modulation, with a concatenated detection and decoding scheme. Simulation results confirm that multidimensional constellations that satisfy KPIs of a certain channel scenario outperform others. Moreover, the bit error rate performance of uncoded systems, and the performance of the coded systems are coupled to their bit-labeling. The performance of the systems also remarkably depends on the behavior of the multi-user detector at different signal-to-noise ratio regions.

Resource Allocation-Based PAPR Analysis in Uplink SCMA-OFDM Systems

Abstract: Sparse code multiple access (SCMA) is a non-orthogonal multiple access (NOMA) uplink solution that overloads resource elements (RE's) with more than one user. Given the success of orthogonal frequency division multiplexing (OFDM) systems, SCMA will likely be deployed as a multiple access scheme over OFDM, called an SCMA-OFDM system. One of the major challenges with OFDM systems is the high peak-to-average power ratio (PAPR) problem, which is typically studied through the PAPR statistics for a system with a large number of independently modulated sub-carriers (SCs). In the context of SCMA systems, the PAPR problem has been studied before through the SCMA codebook design for certain narrowband scenarios, applicable more for low-rate users. However, we show that for high-rate users in wideband systems, it is more meaningful to study the PAPR statistics. In this paper, we highlight some novel aspects to the PAPR statistics for SCMA-OFDM systems that is different from the vast body of existing PAPR literature in the context of traditional OFDM systems. The main difference lies in the fact that the SCs are not independently modulated in SCMA-OFDM systems. Instead, the SCMA codebook uses multi-dimensional constellations, leading to a statistical dependency between the data carrying SCs. Further, the SCMA codebook dictates that an UL user can only transmit on a subset of the available SCs. We highlight the joint effect of the two major factors that influence the PAPR statistics - the phase bias in the multi-dimensional constellation design along with the resource allocation strategy. The choice of modulation scheme and SC allocation strategy are static configuration options, thus allowing for PAPR reduction opportunities in SCMA-OFDM systems through the setting of static configuration parameters. Compared to the class of PAPR reduction techniques in the OFDM literature that rely on multiple signalling and probabilistic techniques, these gains come with no computational overhead. In this paper, we also examine these PAPR reduction techniques and their applicability to SCMA-OFDM systems.

Sparse Code Multiple Access: Potentials and Challenges

Abstract: The massive connectivity is among other unprecedented requirements which are expected to be satisfied in order to follow the perpetual increase of connected devices in the era of Internet of Things. In contrast to the family of conventional orthogonal multiple access schemes, the key distinguishing feature of non-orthogonal multiple access (NOMA) is its capacity to support the massive connectivity. Sparse code multiple access (SCMA) is one of the powerful schemes of code-domain NOMA (CD-NOMA) and is among the promising candidates of multiple access techniques to be employed in future generations of wireless communication systems thanks to the sparsity pattern of its codebooks. This technique has been actively investigated in recent years. In this paper, we provide a comprehensive survey of the state-of-the-art of SCMA. First, we will pinpoint SCMA place in the NOMA landscape including power-domain NOMA and CD-NOMA with the aim of justifying why SCMA is prominent. Then, its system architecture is highlighted and its basic principles are presented, afterwards a review of exiting codebook designs and available SCMA detectors is provided, before showing how resources are expected to be assigned, and how SCMA can be combined with other existing and emerging technologies. Finally, we present a range of future research trends and challenging open issues that should be addressed to optimize SCMA performance.

RFF Based Detection for SCMA in Presence of PA Nonlinearity

Abstract: The next-generation of communication systems must be capable of serving a significantly higher traffic generated by a large number of devices. To support massive connectivity over limited time-frequency resources, several non-orthogonal multiple access (NOMA) paradigms have emerged. In this context, sparse code multiple access (SCMA) based NOMA is particularly attractive due to its robustness to error-propagation, and its potentially high coding-gain with appropriate codebook design. However, the performance of SCMA based systems is severely degraded by distortions introduced by non-ideal hardware, e.g. power-amplifier (PA) nonlinearity. To mitigate such artefacts, in this letter, a random Fourier feature (RFF) based hybrid message passing algorithm (MPA) is proposed, and validated through computer simulations. Lastly, an analytical proof is presented that indicates that the use of RFFs significantly improves the convergence of the MPA in the presence of impairments, and renders error-rate performance equivalent to that of a linear Gaussian channel under approximate MPA.