Uplink Sparse Code Multiple Access System Research Articles

Cross-Layer Codebook Allocation for Uplink SCMA and PDNOMA-SCMA Video Transmission Systems and a Deep Learning-Based Approach

Sparse code multiple access (SCMA) and power-domain nonorthogonal multiple access (PDNOMA) have been considered for use with fifth-generation (5G) and beyond mobile communications, in order to increase the bandwidth efficiency, reduce the latency in terms of waiting for resources, and increase the numbers of connections. Existing codebook allocation schemes for SCMA and PDNOMA-SCMA systems consider only the physical layer. We propose an iterative cross-physical-and-application-layer codebook allocation for uplink video communications. We allocate the codebook according to the channel state information of the physical layer, and codebooks are exchanged among users to minimize the sum of the video mean square error in order to increase the average peak signal-to-noise ratio (PSNR). Furthermore, we propose a deep neural network (DNN) approach to reduce the computational complexity. We propose a novel postprocessing algorithm that is applied to the DNN output to ensure the constraints of codebook allocation are satisfied. Simulation results show that the proposed iterative PDNOMA-SCMA cross-layer codebook allocation scheme outperforms an existing scheme that uses only the physical layer by 1.27 dB in terms of PSNR (video quality) for 12 users, four subcarriers, and SNR = 21 dB. The proposed DNN-based approach has an execution time that is 67% lower than the proposed iterative PDNOMA-SCMA cross-layer codebook allocation scheme, at the cost of a performance degradation of 0.84 dB.

Deep Neural Network Aided Low-Complexity MPA Receivers for Uplink SCMA Systems

Sparse code multiple access (SCMA) has exhibited superiority in spectrum efficiency, which is particularly essential in the Internet of Things (IoT) system where a steadily increasing number of device connections are accommodated. However, the computational complexity of the conventional message passing algorithm (MPA) for the multiuser SCMA detection increases exponentially with the degree of resource nodes (RNs). To address this issue, two low complexity MPA schemes are proposed by utilizing the sparse feature of codewords. First, a sorted MPA (SMPA) detector is introduced to reduce the message exchanging from RNs to variable nodes (VNs) by dropping the redundant superposed constellation points outside a belief interval. Next, in order to further speed up the sorting process of the Euclidean distances between the received signal and codeword combinations, a deep neural network aided MPA (DNNMPA) is proposed, in which, the DNN behaves as a function approximator to generate the belief interval and operates in parallel with the initialization procedure before iterative message passing. Simulation results illustrate that the proposed SMPA and DNNMPA detectors significantly reduce the computational complexity of the conventional MPA one, but with comparable decoding capabilities, for the uplink SCMA system.

Joint uplink SCMA codebook design for correlated fading channels

Sparse Code Multiple Access (SCMA) is currently one of the most intensively investigated Multicarrier Non-Orthogonal Multiple Access (NOMA) technology for 5G wireless communication system. Careful design of SCMA codebook is one of the major performance criteria of uplink SCMA systems. We took the challenge of tackling SCMA Codebook design problem in correlated Rayleigh fading channels. We propose a novel joint codebook design approach followed by a new signal model, where the design problem is posed as a Quadratically Constrained Quadratic Program (QCQP) which is dealt using Matrix-lifting Semidefinite Relaxation (MSDR). Extensive numerical simulations are presented to provide the validity of proposed codebook comparing with some other well known designs.

An Efficient Codebook Design for Uplink SCMA

Sparse code multiple access (SCMA) is one of the most intensively investigated non-orthogonal multiple access (NOMA) techniques for the fifth generation communication (5G) system. In this paper, a new multi-stage optimization approach for codebook design is proposed for the uplink SCMA system. The proposed schemes includes two parts: i) multi-dimensional mother constellation design ii) mapping matrix design. Firstly, the multi-dimensional complex mother constellation design is implemented by a series of two-dimensional real constellations which can be obtained by the lattice theory and the symbol switch algorithm (SSA). The Secondly, we construct user-specific mapping matrix by optimizing the phase rotation of the user constellation to effectively reduce the interference between the multi-user codewords superimposed on every single time-domain resource elements (REs). Finally, the multi-user codebooks are generated by combining the multi-dimensional mother constellation and the user-specific mapping matrix. The simulation results demonstrate that the proposed codebooks can greatly decrease bit error rate (BER) value compared to the existing codebooks under different channels, different codebook sizes and different overloading ratios, and the performance is also improved for the large-scale SCMA codebook. More importantly, in order to verify the proposed codebook applicability, two different message passing algorithm (MPA) are used to simulate the SCMA system with different codebook sizes, both of which obtain faster convergence speed and better BER performance than other existing codebooks.

User capacity for uplink SCMA system

Sparse Code Multiple Access (SCMA) is a non-orthogonal multiple access (NOMA) scheme which allows multi-user communication with massive connectivity. In this paper, we consider an uplink SCMA network of limited resources (time/frequency/power). We seek to answer the following question: what is the maximum number of users that can be admitted in uplink SCMA subject to user-rate constraints? This is termed “user capacity” in communication network. We first obtain a closed form for the lower bound of user capacity which is the first contribution of this work. We then study the general problem of optimizing the resource allocation in terms of codebook assignment and power allocation to maximize the number of users, as well as the total sum rate subject to power, codebook and user-rate constraints. This optimization problem turns out to be non-convex and NP-hard; therefore, we propose an iterative algorithm that provides sub-optimal codebook assignment and power allocation which can efficiently solve this problem. Specifically, another contribution of this work is showing that using swap matching for codebook assignment and Difference of two Convex functions (DC) programming for power allocation efficiently solve the problem yielding better results compared with, e.g., cooperative co-evolutionary particle swarm optimization (CCPSO) algorithm or simple equal power and conventional codebook allocation. Finally, we verify our analytical bound on the user capacity via Monte Carlo simulations and show that the proposed resource allocation algorithm provides significant gains in the number of scheduled users in the system with higher sum rate compared with other schemes. The proposed algorithm can achieve an increment in the number of scheduled users of 45%, and 80% compared with CCPSO and simple equal power and regular codebook allocation, respectively. We also compare our proposed swap matching criterion based on sum rate maximization with the two-sided exchange stable swap matching and simulation results show the effectiveness of the proposed criterion for our problem.

Edgewise Serial Message Passing Detection of Uplink SCMA Systems for Better User Fairness and Faster Convergence Rate

Sparse code multiple access (SCMA) is a promising non-orthogonal multiple access (NOMA) scheme proposed for the upcoming 5G system. Multiuser detection using the message passing algorithm (MPA) with parallel and serial schedules has been considered for SCMA systems. Although serial schedules provide faster convergence rates compared to the parallel schedule, the existing user-wise serial MPA detectors are found to have a user unfairness phenomenon in terms of BER performance, especially at small iteration numbers. To address this issue and to further accelerate the convergence rate, this letter proposes a class of edgewise serial schedules (ESSs). Simulations results demonstrate that optimized ESSs can not only improve the user fairness significantly but also achieve faster convergence rate compared to user-wise serial schedules.

Performance analysis of 5-ary MUSA and SCMA for uplink transmission

<p>Multiple access is one of the core technologies of wireless communications, which enables wireless base stations to deal with a large number of different users and provide the service for each of them at the same time. Meeting the 5G challenges, non-orthogonal multiple access is the main concerned point in 5G technologies. In this paper, two types of non-orthogonal multiple access schemes, namely, 5-ary Multi User Shared Access (MUSA) and Sparse Code Multiple Access (SCMA), are studied. The Bit Error Rate performance (BER) analysis in terms of user overloading for an uplink 5-ary MUSA and SCMA systems are analyzed.</p>

Scheduling and Layer Selection Based Performance Improvement of Uplink SCMA System With Receive Beamforming

A modified uplink sparse code multiple access (SCMA) scheme with receive beamforming is herein proposed. Although a base station equipped with multiple antennas can support many users simultaneously using multi-beams, the complexity of the optimal SCMA system may be too large to be implemented in view of a practical system. Therefore, a two stage SCMA system with receive beamforming is proposed, based on uplink scheduling and three step layer selection. Analysis and simulation results of the proposed scheme showed the advantage of large complexity reduction with little performance degradation.

Device-to-Device Communications Underlaying an Uplink SCMA System

Device-to-device (D2D) communication has been a potential solution to improve spectral efficiency of cellular systems due to frequency resource sharing. This paper considers D2D communications underlaying an uplink cellular system enabling sparse code multiple access (SCMA) technology, where the base station (BS) can decode the signals of cellular users without mutual interference. The demands for high data rate as well as low latency in massive connectivity is the main challenging requirement in D2D communications, along with ensuring the quality of service (QoS) for the on-running cellular user equipment (CUEs). To tackle the problem, the BS is designed to first assigns the codewords in a codebook to CUEs based on the lower bound of the achievable CUE rates, so that the sum rate (SR) of CUEs is maximized. With the usage of mutual-interference suppression in the SCMA-enabled system, the BS then attempts to maximize the SR of D2Ds in a transmission block through a joint power and resource allocation subject to the QoS requirements for both CUEs and D2Ds. This task is formulated as a mixed-integer non-convex programming. We propose a low-complexity two-phase algorithm of joint heuristic and inner approximation method to efficiently solve the problem. The numerical results verify that the codebook assignment problem based on the lower bound of SR is easily solved, and the proposed algorithm to maximize the SR of D2Ds outperforms existing methods.

Gaussian Approximation-Based Belief Propagation Receiver for Uplink SCMA Systems With Imperfect CSIR

For uplink sparse code multiple access (SCMA) systems, a channel estimation is required to support a multi-user detection in practice. Motivated by the conventional detection, called a Gaussian approximation-based belief propagation (GA-BP) with matched filtering, we propose an efficient receiver suitable for the uplink SCMA systems when exact channel state information is not available. By estimating matched filtered channels (rather than explicitly estimating actual channels), the proposed methods efficiently support the second-stage GA-BP detector with negligible increment of complexity. The simulation results show that the proposed receiver achieves the similar estimation and detection performance to the state-of-the-art receiver while the required complexity can be drastically reduced.

Codebook Optimization for the Superposition Transmission of Uplink SCMA Systems

For an uplink sparse code multiple access (SCMA) system, a codebook-domain superposition transmission can be applied to increase the multiplexing gain by efficient utilization of the codebooks as multiple access resources. However, the destructive collision of superposed codewords can restrict the performance improvement of the system because of the increasing interlayer interferences. In this paper, we analyze the effects of the interlayer interferences on the bit error rates, and optimize the SCMA codebooks that can mitigate the interlayer interferences. Simulation results show that the optimized codebooks can provide a noticeable gain to improve the performance of uplink SCMA systems applied with superposition transmission.

Resource-Selection Based Low Complexity Detector for Uplink SCMA Systems With Multiple Antennas

Sparse code multiple access (SCMA) is a novel non-orthogonal multiple access scheme for 5G systems, in which based stations are usually equipped with multiple antennas. In this letter, we propose a novel resource-selection based message passing algorithm (RSB-MPA) detector for uplink SCMA systems with multiple receive antennas. In the proposed RSB-MPA detector, several resources are selected to perform the Jointly Gaussian Algorithm and the remaining are to perform the maximum likelihood algorithm. The resource selection criterion is based on the minimum distance at each resource, which is lower bounded by the minimum singular value of the corresponding channel matrix. Simulation results show that the RSB-MPA detector can significantly reduce the computational complexity with slight performance degradation.

Outage Probability Region and Optimal Power Allocation for Uplink SCMA Systems

As a promising non-orthogonal multiple access scheme, sparse code multiple access (SCMA) technology has attracted much attention. Because inter-user interference is present in code domain and multi-user iterative detection is required, user capacity and outage probability analysis for uplink SCMA systems are challenging and have not been presented in the literature. In this paper, the capacity region for uplink SCMA systems is analyzed, based on which the common and individual outage probability regions are calculated. Optimizing the outage probability within the outage probability region can be casted as an Lagrangian duality problem and solved by an iterative descent algorithm, which however imposes high complexity since the expectation operation is required in each iteration. To reduce the computational complexity of solving this Lagrangian duality problem, an adaptive algorithm is developed, which is capable of providing the optimal outage probability and adaptively updating it. Furthermore, a power allocation policy is naturally obtained to achieve the optimized outage probability in the outage probability region.

Sparse Structure-Based Channel Estimation for Uplink SCMA System

To fully utilize the performance gain of sparse code multiple access (SCMA) system, the channel state information of multiusers must be obtained at the base station. However, conventional channel estimation approach causes significant training overhead as the number of active users becomes large. In this paper, we propose a channel estimation scheme for the uplink SCMA system to reduce the training overhead, which is based on the unstructured channel estimator (UCE). However, it is ineffective in terms of the resource usage to apply the UCE scheme to the SCMA system directly since the data detection requires only channel information on the nonzero subcarriers of the SCMA codeword. Thus, we introduce a sparse pilot structure where the location of nonzero pilot symbols correspond to the location of nonzero symbols in the SCMA codeword and provide an optimal pilot allocation scheme for the sparse pilot structure, which can achieve the mean square error lower bound. In addition, we consider the codebook reuse scenario to support more users with the existing SCMA codebooks. While the codebook reuse can help realize the massive connectivity, it has a problem that interference on each resource grows irregularly, which in turn leads to overwhelming training overhead. To solve this problem, we propose a channel estimation approach to reduce interference per subcarrier uniformly by the weight-regularization (WR) algorithm, and apply the optimal pilot allocation and least squares algorithm. The puncturing channel information by the WR algorithm can be obtained by a minimum mean square error (MMSE) interpolator or a combined interpolator. Analytical results and simulations shows effectiveness of the proposed channel estimators.

Uplink SCMA System With Multiple Antennas

Sparse code multiple access (SCMA) is a codebook-based nonorthogonal multiple access that exploits the coding gain of designed codebooks and the near-optimum performance of belief-propagation (BP) detection. In this paper, we study an uplink SCMA system equipped with multiple receive antennas utilized to get a diversity gain. Assuming that the maximum likelihood detection is applied to the system, we derive the upper bound on the average bit error rate (ABER) and analyze the diversity order which is shown to be the product of the number of receive antennas and the spreading gain. Exploiting the multiple received signals, we also propose a simplified detection method called Gaussian approximation based BP (GA-BP) detection with linear prefiltering . As the first step of the proposed detection, a conventional linear filter is applied to mitigate the multiuser interferences. Then, the GA-BP iteratively removes the residual interferences which may be approximated to a Gaussian random variable for the massive number of user equipments. Numerical results show that for moderate and high signal to noise ratio region the analyzed upper bounds on ABER of SCMA system tightly coincide with the simulation results. Also, for the moderate numbers of antennas, the ABER of GA-BP with matched filter closely approaches to that of the conventional BP detection with much lower computational costs.

Backtracking Codebook Matching Algorithm Based on Codebook Correlation for Uplink SCMA System

In this letter, we have investigated the frequency diversity gain of a sparse code multiple access (SCMA) system to improve spectrum utilization by exploiting the codebook correlation in the SCMA system. To this end, a backtracking codebook matching (BCM) algorithm is proposed, whereby there are more successfully scheduled users, which are allocated the low-correlated codebooks. Simulation results exhibit the superiority of the BCM algorithm and the impact of codebook correlation on scheduling.

Optimized multiuser detection algorithm for uplink SCMA system

Sparse code multiple access (SCMA) is a competitive nonorthogonal access scheme for the next mobile communication. As a multiuser sharing system, SCMA adopts message passing algorithm (MPA) for decoding scheme in receiver, but its iterative method leads to high computational complexity. Therefore, a serial message passing algorithm based on variable node (VMPA) is proposed in this paper. Making some subtle alterations to message update in original MPA, VMPA can greatly reduce overall computing complexity of decoding scheme. Furthermore, considering that serial structure may increase decoding delay, a novel grouping scheme based sparse matrix is applied to VMPA. Simulation results verify that the new algorithm, termed as grouping VMPA (G-VMPA), can achieve a better tradeoff between bit error rate (BER) and computing complexity than MPA.

A Fast Convergence Multiuser Detection Scheme for Uplink SCMA Systems

Sparse code multiple access (SCMA) is a competitive non-orthogonal multiple access technique for fifth generation wireless communication networks which can accommodate massive connectivity. Among the existing multiuser detection schemes for uplink (UP) SCMA systems, the asynchronous message passing algorithm (ASYN-MPA) scheme, where messages are updated sequentially, generally converges faster than the synchronous variant, where all messages are updated in parallel manner. Nevertheless, the specific pre-defined order of the ASYN-MPA scheme is not always the best option. In this letter, we tackle the problem of how to schedule message for the ASYN-MPA scheme that results in the best convergence rate. Specifically, a novel residual-aided message propagation approach for scheduling messages in the ASYN-MPA scheme, termed residual-aided MPA, is proposed for UP SCMA systems, which exploits the dynamic selection of the message which has the largest residual. Simulations show that the proposed scheme with two iterations provides very similar bit error rate performance to the existing multiuser detection schemes with six iterations (only less than 0.05 dB degradation), whose complexity is reduced substantially.

Shuffled Multiuser Detection Schemes for Uplink Sparse Code Multiple Access Systems

The existing multiuser detection schemes for uplink (UP) sparse code multiple access (SCMA) systems are based on a parallel message update for message passing algorithm (MPA). In this letter, a shuffled MPA (S-MPA) scheme for UP SCMA systems is proposed, based on a serial message update strategy. Since the updated messages can join the message propagation immediately in current iteration, the convergence rate is accelerated, so that the complexity of the proposed S-MPA scheme can be substantially reduced with negligible bit error rate (BER) degradation. Simulations show that the proposed S-MPA scheme with two iterations provides similar BER performance to the original MPA scheme with six iterations. Furthermore, a parallel form of the proposed S-MPA scheme, termed group S-MPA, is developed to decrease the detection delay of the proposed S-MPA scheme, which offers a good BER-latency tradeoff.

A Fixed Low Complexity Message Pass Algorithm Detector for Up-Link SCMA System

Sparse code multiple access (SCMA) is a new modulation and non-orthogonal multiple access scheme for 5G systems, in which the coded bits are mapped to multi-dimensional sparse codewords, and the message passing algorithm (MPA) is employed to detect multi-user signals. However, the relative high computational complexity of MPA detection is still a big concern for practical implementation, even the sparse structure has already been employed. In this letter, a novel fixed low complexity detector for uplink SCMA system is proposed, based on partial marginalization (PM). Our analysis and simulation results show that, compared with the existing MPA detector, the implementation complexity of the new PM-based detector is reduced substantially, while the bit error ratio (BER) performance degrades unnoticeably (less than 0.3 dB).