Performance Analysis of Maximum-Correntropy Based Detection for SCMA

Recently, sparse code multiple access (SCMA) is proposed as one of the important candidacies for the fifth generation (5G) radio access technique. SCMA is a non-orthogonal multiple access (NOMA) technique which allows multiple users share the same radio resource and thus increase spectral efficiency largely. In SCMA, a set of binary coded bits is mapped directly into a complex vector by use of a predefined multi-dimensional codebook. The sparsity of the codewords makes the near-optimal detection feasible through iterative message passing algorithm (MPA). The pursuit of higher spectral efficiency motivates us to study the performance of multiple-input-multiple-output (MIMO) SCMA system in this paper. Simulation results show that compared with the conventional MIMO-OFDM system, MIMO-SCMA can provide a gain up to 50% in data throughput with the aid of MPA technique.

The implementation of Multiple Input Multiple Output (MIMO) on the Sparse Code Multiple Access (SCMA) can enhance performance in 5G future communication. Low complexity detector for the MIMO-SCMA system to achieve near-optimum bit error rate (BER) performance is still hot topic in this research field. This paper is investigate low complexity MIMO-SCMA detector by combining a joint factor graph (JFG) and sphere decoding (SD) algorithm based on message passing algorithm (MPA) called by SD-JFG-MPA. SD-JFG-MPA is combine n-th single factor graph become one virtual factor graph to deal with MIMO detector. SD algorithm is used to reduce high complexity of the JFG-MPA by calculating possible combination codeword within search radius R SD . SD-JFG-MPA is investigated under Rayleigh channel model with overloading factor 150%. The simulation result shows that complexity and BER performance is determined by a selected radius of SD-JFG-MPA. Optimum performance with less processing time for one bit error on single SCMA when $R_{SD} = \sqrt {E_b} \times 3/2 \times r_{max}$ meanwhile for 2x2 MIMO-SCMA when $R_{SD} = \sqrt {E_b} \times N_{mimo} \times r_{max}$. 2×2 MIMO-SCMA performance is better with 5 dB gap at BER = 10−3 compared to single SCMA.

Sparse code multiple access (SCMA) is a promising non-orthogonal multiple access (NOMA) scheme for massive machine-type communications for 5G-and-beyond communication systems. Innovative use of orthogonal frequency division multiplexing with index modulation (OFDM-IM) takes advantage of using tone indices in data transmission. In this study, we propose a novel multiplexing and multiple access scheme, namely SCMA based on OFDM-IM (SCMA-IM). SCMA-IM method can be implemented in uplink NOMA systems in an efficient way with similar computational complexity as SCMA. In this method constellation differences and diversity are obtained via SCMA codebooks (CBs) and the employment of CBs is transferred to index modulation (IM). Performance improvement is achieved via CBs so that the number of data bits carried by indices increases more than one bit with different constellations, and also with the number of CBs assigned. In order to determine the indices used in IM, the receiver structure is simplified by the message passing algorithm and log-likelihood ratio detection process used in SCMA receivers without indexing the receiver. Thus, a new NOMA scheme is obtained by coding with IM. Bit error rate performance of the system is studied for 150% and 200% overloading factors.

Different from traditional communication systems, information-centric Internet of things (IC-IoT) as a novel smart paradigm needs to guarantee end-to-end connectivity for rapidly growing smart devices. How to meet the demands of massive connection has become a key problem for IC-IoT. Sparse code multiple access (SCMA) as a code-domain non-orthogonal multiple access (NOMA) technique has been intensively investigated. With SCMA, each user employs different sub-carrier frequencies for transmission, and different users can share the same sub-carrier frequency via superposition coding. The spectrum efficiency is thus improved. However, designing large-scale codebook sets is still an open problem for SCMA. In this paper, a new lattice-based codebook design method is proposed via mother constellation optimization. First, the optimization problem of the mother constellation is formulated. Through analysis, the problem can be converted into two sub-problems. Accordingly, we first use the lattice theory to find a constellation containing infinite points with large coding gain. After that, we search for a boundary that contains a set of points via spherical packing. Such an approach enables us to obtain a real constellation satisfying a power saving criterion. Secondly, the mother constellation with large power variance is obtained from the real multi-dimensional constellation. Finally, lattice-based codebooks are generated by combining the mother constellation and the mapping matrices with constellation rotation. Simulations demonstrate that the designed codebooks have improved bit error rate (BER) performance with large codebook size, especially at high signal to noise ratio (SNR).

5 G networks may not be competent in fully supporting the high data rates, system capacity, and spectral efficiency expected in the upcoming 6 G networks. An enabling factor to achieve these requirements is the adoption of the Sparse Code Multiple Access (SCMA), which is one of the most promising code-domain Non-Orthogonal Multiple Access (NOMA) techniques. Nowadays, there are two major challenges for the implementation of SCMA in practical networks. First, the design of a near-optimal codebook set at the transmitter, that heavily impacts the network performance. Second, an efficient decoding algorithm at the receiver, that dominates the computational complexity of the system. The two aspects are not independent from each other; therefore the optimization of an SCMA network should address jointly both the Encoder and the Decoder side. Moreover, such solution is far from optimal when designed for general purpose use, since it does not exploit the channel statistical information known at the transmitter and the receiver side. However, most of the works available in the literature address only one aspect and also are not tailored for a given radio channel. In this paper, we design an end-to-end SCMA en/deconding structure based on the integration between a state-of-the-art AutoEncoder (AE) architecture and a novel Wasserstein Generative Adversarial Network (WGAN). The aim is to jointly create a near-optimal codebook design and a non-computationally heavy Decoder that are robust to the given channel statistics. Finally, we trained our model to be flexible to support different channel conditions and compared its performance against the state-of-the-art AE and the best conventional Decoders. The simulation results show that our innovative design exhibits decoding performance very similar to conventional Decoders with a reduced decoding latency.

Sparse code multiple access (SCMA), as a codebook-based non-orthogonal multiple access (NOMA) technique, has received research attention in recent years. The codebook design problem for SCMA has also been studied to some extent since codebook choices are highly related to the system's error rate performance. In this paper, we approach the SCMA codebook design problem by formulating an optimization problem to maximize the minimum Euclidean distance (MED) of superimposed codewords under power constraints. While SCMA codebooks with a larger MED are expected to obtain a better BER performance, no optimal SCMA codebook in terms of MED maximization, to the authors' best knowledge, has been reported in the SCMA literature yet. In this paper, a new iterative algorithm based on alternating maximization with exact penalty is proposed for the MED maximization problem. The proposed algorithm, when supplied with appropriate initial points and parameters, achieves a set of codebooks of all users whose MED is larger than any previously reported results. A Lagrange dual problem is derived which provides an upper bound of MED of any set of codebooks. Even though there is still a nonzero gap between the achieved MED and the upper bound given by the dual problem, simulation results demonstrate clear advantages in error rate performances of the proposed set of codebooks over all existing ones not only in AWGN channels but also in some downlink scenarios that fit in 5G/NR applications, making it a good codebook candidate thereof. The proposed set of SCMA codebooks, however, are not shown to outperform existing ones in uplink channels or in the case where non-consecutive OFDMA subcarriers are used. The correctness and accuracy of error curves in the simulation results are further confirmed by the coincidences with the theoretical upper bounds of error rates derived for any given set of codebooks.

Non-orthogonal multiple access (NOMA) is one promising technology, which provides high system capacity, low latency, and massive connectivity, to address several challenges in the fifth-generation wireless systems. In this paper, we first reveal that the NOMA techniques have evolved from single-carrier NOMA (SC-NOMA) into multi-carrier NOMA (MC-NOMA). Then, we comprehensively investigated on the basic principles, enabling schemes and evaluations of the two most promising MC-NOMA techniques, namely sparse code multiple access (SCMA) and pattern division multiple access (PDMA). Meanwhile, we consider that the research challenges of SCMA and PDMA might be addressed with the stimulation of the advanced and matured progress in SC-NOMA. Finally, yet importantly, we investigate the emerging applications, and point out the future research trends of the MC-NOMA techniques, which could be straightforwardly inspired by the various deployments of SC-NOMA.

ABSTRACTFor the next‐generation communication systems, to improve spectral efficiency and increase the data rate, new multiple access techniques have been investigated. Orthogonal multiple access techniques are widely used in traditional communication systems while nonorthogonal multiple access (NOMA), proposed in 5G, has been a promising technology for satisfying the demand for future wireless communication networks. Sparse code multiple access (SCMA) is a code‐domain NOMA method that provides diversity gain with signal constellation coding. However, to increase the performance of SCMA, there are only limited works provided in the literature in terms of codebook design and receiver design. In this paper, a new multiple‐access model is proposed by applying various diversity techniques for downlink SCMA. The performance of the proposed model is evaluated with both computer simulations and theoretical analysis. Results show that the proposed model provides a 1.6 dB gain in terms of the bit error rate (BER) under the Rayleigh fading channel.

Sparse Code Multiple Access (SCMA) is a class of competitive non-orthogonal multiple access (NOMA) that is proposed to support massive Machine Type of Communication (m-MTC). In this paper, we propose a new scheme to construct the SCMA codebooks, where we jointly optimize the rotation angles and mother codebook parameters. The basic idea is to make the upper bound of the error probability as smaller as possible. To realize it, we search for suitable angles and parameters through the bare bones particle swarm optimization (BBPSO) algorithm. The simulation results demonstrate that compared with the original SCMA, Star-QAM SCMA and LDS the new proposed SCMA codebooks provides better performance in both additive white Gaussian noise (AWGN) and Rayleigh channels, moreover, it also gives better performance in high overloading.

Sparse Code Multiple Access (SCMA) is a promising non-orthogonal multiple access (NOMA) technique in future wireless communications. In this letter, a novel uplink codebook optimization method for SCMA using evolution strategies is proposed. Unlike traditional multi-stage codebook designs, we use a single-stage codebook construction method and directly optimizes the entire codebook. Fitness functions suitable for different uplink channels are proposed to jointly optimize various key metrics in the corresponding channels. By comparing our codebooks with various benchmark codebooks, simulation results show that the proposed method can significantly reduce the bit error rate in various uplink channels.

Sparse code multiple access (SCMA) is an up-and-coming non-orthogonal multiple access technology. The message passing algorithm (MPA) is utilized for multi-user signal detection in the SCMA system to achieve a performance close to the maximum a posterior algorithm. However, higher iterations will lead to the higher computational complexity of the MPA. In this paper, a dynamic threshold and stability judgment based MPA scheme (DTS-MPA) is proposed to reduce the computational complexity by simplifying the factor graph and reducing the number of iterations. Firstly, an adaptive dynamic threshold is set to minimize the number of iterations in the different channel state information. Secondly, an additional iteration is proposed to determine whether the variable nodes that meet the dynamic threshold reach stable convergence to improve the decoding reliability. Variable nodes that meet the above conditions will be decoded in advance. Numerical results show that the DTS-MPA can significantly reduce the computational complexity of the MPA and achieve a significant trade-off between bit error rate performance and computational complexity.

Sparse code multiple access (SCMA) is a newly proposed non-orthogonal multiple access technique for the 5th generation (5G) of wireless communication systems. It improves low-density signature multiple access (LDSMA) by replacing the inherent repetition code with multi-dimensional constellations. In this paper, the Gaussian-input channel capacities as well as the constellation constrained (CC) capacities of SCMA and LDSMA are analyzed and compared for the cases of Gaussian multiple access channel (GMAC) with random phase rotation and GMAC with fast fading, which disclose the performance potential of SCMA over LDSMA.

Sparse code multiple access (SCMA) is one of the most concerned non-orthogonal multiple access schemes in 5G communication system. Meanwhile, device-to-device (D2D) communication is also one of the key technologies for 5G network to improve the spectral efficiency. In cellular systems with SCMA, the non-orthogonal nature renders resource blocks support for more users so that an overloaded system can be achieved. To further improve the system capacity, a D2D and uplink cellular coexisting network is proposed in this paper. The interference between D2D and cellular users are handled. Since conventional message passing algorithm (MPA) has the exponential complexity, the receiver for cellular users is based on some low complexity methods and that for D2D users is also associated with this method. Simulation results show that the proposed hybrid network has an acceptable BER performance loss compared to the general uplink SCMA system, while the proposed SCMA receiver can reduce the decoding complexity significantly compared to the conventional MPA.

Sparse code multiple access (SCMA) is a new non-orthogonal multiple-access technique in future wireless networks. In SCMA uplink burst transmission, user detection and channel estimation require significant pilot overhead. Dispersive channels with relative small coherent frequency / time, as well as fading diversity techniques, both lead to a result that multiple fading blocks are taken during one transmission. In this paper, a new method of separating SCMA user detection and channel estimation among different fading blocks in dispersive channels is proposed to reduce pilot overhead. Further more, according to the sparsity of SCMA codebooks, a new mapping pattern from SCMA layers to physical resources is proposed to improve channel estimation performance with given pilots. The effectiveness of the proposal are described and analyzed, meanwhile the complexity is evaluated. Numerical simulations are performed to substantiate the performance of the proposed algorithm.

Sparse Code Multiple Access (SCMA) is a promising code-based multiple access technique for achieving higher spectral efficiency and massive connectivity that is crucially required in the B5G applications such as massive machine-type communication (mMTC). Traditional SCMA receivers use Maximum Likelihood (ML) and Message Passing Algorithm (MPA) for signal decoding, which nonetheless suffer from extremely high computational complexity. To resolve the issue, we propose to use Graph Neural Networks (GNN) to replace MPA for decoding, aiming at reducing the decoding complexity while maintaining satisfactory Bit Error Rate (BER) performance. Simulation results show that our proposed solution can achieve much higher decoding accuracy and faster decoding speed.