Sparse code multiple access (SCMA) is a novel type of non-orthogonal multiple access technology that combines the concepts of CDMA and OFDMA. The advantages of SCMA include high capacity, low time delay, and high date rate. In this paper, a power allocation algorithm is proposed for SCMA downlink systems where each tone is taken by more than one user to maximize the system's sum capacity. In SCMA systems, users are divided into different user groups. Thus, our proposed algorithm includes three-level power allocation. Since the power allocation problem is non-convex, the complexity of finding the optimal solutions is prohibitive. The Lagrange dual decomposition method is employed to efficiently solve the non-convex optimization problem. Results show that the optimized algorithm can significantly improve the sum capacity.

Sparse code multiple access (SCMA) is a promising non-orthogonal air-interface technology for its ability to support massive connections. In this paper, we design the multiuser codebook and the advanced decoding from the perspective of the theoretical capacity and the system feasibility. First, different from the lattice-based constellation in point-to-point channels, we propose a novel codebook for maximizing the constellation constrained capacity. We optimize a series of 1-D superimposed constellations to construct multi-dimensional codewords. An effective dimensional permutation switching algorithm is proposed to further obtain the capacity gain. Consequently, it shows that the performance of the proposed codebook approaches the Shannon limit and achieves significant gains over the other existing ones. Furthermore, we provide a symbol-based extrinsic information transfer tool to analyze the convergence of SCMA iterative detection, where the complex codewords are considered in modeling the a priori probabilities instead of assuming the binary inputs in previous literature. Finally, to approach the capacity, we develop a low-density parity-check code-based SCMA receiver. Most importantly, by utilizing the EXIT charts, we propose an iterative joint detection and decoding scheme with only partial inner iterations, which exhibits significant performance gain over the traditional one with separate detection and decoding.

This paper presents field trial results of innovative air interface technologies: sparse code multiple access (SCMA), filtered orthogonal frequency division multiplexing (f-OFDM), and massive multiple-input multiple-output (MIMO). To confirm the improvement of the promising technologies, the counterparts in long term evolution (LTE) are selected as the comparison baseline. For each technology, detailed parameter configurations and deployment scenarios are addressed at first, then precise test procedures are described, finally, extensive analysis are provided to testify the high spectral efficiency, flexibility and system capacity introduced by the new technologies. According to the trial results, SCMA can achieve 3 times connection number and throughput than SC-FDMA in uplink, and 90% throughput gains over OFDMA in downlink. Waveform f-OFDM is validated to support flexible resources allocation thus avoiding asynchronous transmission in both uplink and downlink. The large number of antennas in Massive MIMO accommodates more user and offers around 10 times throughput than single user scenario in downlink.

Ultrahigh data rate, massive connectivity, ultralow latency, and high reliability, as well as ultraflexible air interface design to support diversified usage scenarios, are the major targets of 5G radio access network design. To meet these targets, advanced new radio transmission technologies, including new waveform, new channel coding, non-orthogonal multiple access, as well as massive antenna techniques, have been proposed and studied worldwide in both academic and industries. Most of the gains claimed in the literature are from simulations or by small scale lab testing. Instead, this paper elaborates on the first hand results and analysis of the large-scale field trials carried out in China for a selection of key 5G technology components as well as some of their combinations, including filtered-orthogonal frequency division multiplexing (OFDM) (f-OFDM), polar code, sparse code multiple access, and massive multi-input multi-output (MIMO) for both uplink and downlink cellular networks. Testing results verify the feasibility and benefit of each technology contributing toward the diversified 5G targets, as well as the feasibility for these technologies to work jointly for higher spectrum efficiency, larger connectivity, and lower latency.

In this paper, we investigate the application of spherical codes in a sparse code multiple access (SCMA) system. We use spherical codes to build multidimensional mother constellations for SCMA codebooks, to lower peak to average power ratio (PAPR) as well as to improve the overall spectrum efficiency. Furthermore, we introduce four approaches to construct good spherical codes. These codes are easy and have large coding gains. We make extensions to some of these spherical codes such that they are suitable for usage in SCMA systems. The performance of the constructed codebooks are compared to known codebooks through simulations, and the numerical results show that spherical codes based codebooks can effectively improve the system performance.

Sparse code multiple access (SCMA) is a new non- orthogonal multiple access scheme, which effectively exploits the shaping gain of multi-dimensional codebook. In this paper, a multi-dimensional SCMA (MD-SCMA) codebook design based on constellation rotation and interleaving method is proposed for downlink SCMA systems. In particular, the first dimension of mother constellation is constructed by subset of lattice Z2. Then the other dimensions are obtained by rotating the first dimension. Further, the interleaving is used for even dimensions to improve the performance in fading channels. In this way, we can design different codebooks for the aim of spectral efficiency or power efficiency. And the simulation results show that the bit error rate (BER) performance of MD-SCMA codebooks outperforms that of the existing SCMA codebooks and low density signature (LDS) in downlink Rayleigh fading channels.

Sparse code multiple access (SCMA) is a code domain non-orthogonal multiple-access technique introduced for future 5G wireless networks. This paper describes the basic ideas of SCMA, the SCMA codebook design, the encoder and decoder, as well as the SCMA enabled transmission schemes for different application scenarios, including uplink grant-free contention-based transmission, downlink multi-user superposition, and downlink open-loop CoMP for ultra-dense networks even with moving users. We shall show from design principles and application examples that SCMA can resolve some major issues of current wireless systems and establish itself as a strong candidate for 5G networks.

Interference alignment (IA) is a well-known transmission strategy for interference channels, with which the sum rate can linearly scale with the number of users at high signal-to-noise ratio (SNR). However, most existing works on IA considered only the maximization of the sum rate without taking into account the bit error rates (BER) performance. In this work, we firstly propose a novel IA algorithm to improve the BER performance for MIMO-OFDM interference channels on a per-subcarrier basis. The proposed IA algorithm is then combined with the sparse code multiple access (SCMA) technique to further enhance the BER performance by exploiting the inherent frequency diversity in the MIMO-OFDM systems. At the receiver, a linear filter is first used to mitigate the inter-user aligned interference and separate the spatial streams, and then an iterative frequency-domain message passing algorithm (MPA) is applied to efficiently separate the overlapped multiple codewords. Simulation results demonstrate that the proposed joint IA and SCMA strategy can provide significant BER gain compared to the existing IA algorithms.

Sparse code multiple access (SCMA) is a non- orthogonal multiple access scheme, which has been considered as one of the key 5G technologies to improve spectral efficiency. Moreover, device-to- device (D2D) communication is introduced as a vital technology component for 5G cellular communication system to improve spectral reuse. D2D communication combined with SCMA will be a significant part of 5G technology to support higher spectral efficiency. However, these benefits depend on efficiently allocating SCMA layers for cellular users and D2D pairs to share corresponding spectrum resources. In this paper, a mapping scheme of users to SCMA layers for D2D communication is proposed to maximize the system sum rate, in which after assigning SCMA layers to cellular users, a coalition game based scheme is proposed to obtain the solution for mapping of D2D pairs to SCMA layers. Simulation results validate the effectiveness of the proposed scheme and show that the proposed scheme outperforms other schemes, and the D2D communication combined with SCMA can obtain significant gain over the one in LTE networks in terms of system sum rate.

In this paper, an optimized codebook design based on rotated angles and extrinsic information transfer (EXIT) chart for a non-orthogonal multiple access scheme, called irregular sparse code multiple access (IrSCMA), is presented. Unlike regular SCMA, in IrSCMA, the defined degree of layer's resource nodes is different, which is beneficial to system performance.It is demonstrated that the new codebook can greatly improve the BER performance especially when the signal-to-noise ratio(SNR) is high, without sacrificing the low detection complexity, compared with the existing codebooks and LDS.

In this paper, we propose a blind estimation method for the antenna mutual coupling matrix and the direction of arrival. First of all, the higher order cumulants based blind estimation method is used to calculate the steering vector of the array. The estimated steering vector can differ from the true steering vector by a factor of -1 or by exchanging of the real and imaginary parts. These differences as well as the direction of arrival and the mutual coupling matrix are estimated afterwards using the least square error criteria. Simulations show the proposed algorithm can converge to the exact solution very quickly and is suitable for the closely aligned antenna arrays for the massive multiple input and multiple output (MIMO) systems.

In this paper, we investigate the Energy Efficiency (EE) - Spectrum Efficiency (SE) tradeoff issue in an OFDM-based cognitive radio (CR) network. A multi-objective resource allocation problem is formulated, where we try to maximize the EE and the SE simultaneously. The Pareto optimal set of the formulated problem is characterized by analyzing the relationship between the EE and the SE. To find a unique globally optimal solution, we proposed a unified EE-SE tradeoff metric, based on which the original optimization task is transformed into a single-objective problem that has a D.C. (Difference of two Convex functions/sets) structure. Then an efficient barrier method is developed, where we speeds up the time-consuming computation of Newton step by exploiting the structure of the D.C. programming problem. Simulation results validate the effectiveness and efficiency of the proposed algorithm. Our general problem formulation sheds some insights on how to design an energy- and spectrum-efficient CR system.

Inter-cell interference management is an notorious issue in cellular communication. Traditionally, static techniques were used to manage the interference: frequency reuse for GSM or universal reuse for CDMA. More recently, fractional frequency reuse for LTE has been common. Based on this idea, the next set of ideas consider coordination among base stations to dynamically manage the interference among the cells. Typically this is done in the context of OFDM systems (LTE), and in particular distributed antenna system (DAS) for LTE (coordinated beamforming). In this paper, the implications of this approach in CDMA systems (example: HSPA+) are discussed. The key idea is that it is not just important to reduce total inter-cell interference, but also the dimension (measured in chips over a spreading sequence length - 16 chips in HSPA) over which the interference is caused. This leads to novel interference management techniques that are specific to CDMA technology, which we term dynamic fractional signature sequence reuse (DFSSR).

In this paper, we evaluate the performance of Multicarrier-Low Density Spreading Multiple Access (MC-LDSMA) as a multiple access technique for mobile communication systems. The MC-LDSMA technique is compared with current multiple access techniques, OFDMA and SC-FDMA. The performance is evaluated in terms of cubic metric, block error rate, spectral efficiency and fairness. The aim is to investigate the expected gains of using MC-LDSMA in the uplink for next generation cellular systems. The simulation results of the link and system-level performance evaluation show that MC-LDSMA has significant performance improvements over SC-FDMA and OFDMA. It is shown that using MC-LDSMA can considerably reduce the required transmission power and increase the spectral efficiency and fairness among the users.

Low density signature orthogonal frequency division multiplexing (LDS-OFDM) is an uplink multi-carrier multiple access scheme that uses low density signatures (LDS) for spreading the symbols in the frequency domain. In this paper, we introduce an effective receiver for the LDS-OFDM scheme. We propose a framework to analyze and design this iterative receiver using extrinsic information transfer (EXIT) charts. Furthermore, a turbo multi-user detector/decoder (MUDD) is proposed for the LDS-OFDM receiver. We show how the turbo MUDD is tuned using EXIT charts analysis. By tuning the turbo-style processing, the turbo MUDD can approach the performance of optimum MUDD with a smaller number of inner iterations. Using the suggested design guidelines in this paper, we show that the proposed structure brings about 2.3 dB performance improvement at a bit error rate (BER) equal to 10-5over conventional LDS-OFDM while keeping the complexity affordable. Simulations for different scenarios also show that the LDS-OFDM outperforms similar well-known multiple access techniques such as multi-carrier code division multiple access (MC-CDMA) and group-orthogonal MC-CDMA.

Low Density Signature-Orthogonal Frequency Division Multiplexing (LDS-OFDM) has been introduced recently as an efficient multiple access technique. In this paper, we focus on the subcarrier and power allocation scheme for uplink LDS-OFDM system. Since the resource allocation problem is not convex due to the discrete nature of subcarrier allocation, the complexity of finding the optimal solutions is extremely high. We propose a heuristic subcarrier and power allocation algorithm to maximize the weighted sum-rate. The simulation results show that the proposed algorithm can significantly increase the spectral efficiency of the system. Furthermore, it is shown that LDS-OFDM system can achieve an outage probability much less than that for OFDMA system.

Using equiprobable M-PAM/QAM constellation instead of Gaussian-distributed signal suffers performance loss, and the ultimate performance loss in high SNR regime is 1.53 dB. In this paper, we propose a new shaping method to optimize equiprobable constellations. The obtained PSK-PAM constellations can achieve performance gain in sense of mutual information by up to 0.3 dB and 0.57 dB over 16 QAM and 64 QAM, respectively. The new constellations are then applied to bit-interleaved coded modulation with iterative decoding (BICM-ID) and the performance gain over M-QAM is verified.

We propose a fast algorithm to compute an initial triangular square-root of the estimation error covariance matrix for BLAST, which are then applied to develop a square-root algorithm for BLAST. The speedups of our square-root BLAST algorithm over the previous square-root BLAST algorithm in the number of multiplications and additions are 3.78-5.8 and 3.95-5 respectively, and the ratios between the computational complexity of our BLAST algorithm and that of the linear MMSE detection algorithm in the number of multiplications and additions are 1.10-0.71 and 0.90-0.71 respectively, which means that for the first time, the nonlinear MMSE BLAST detector with successive interference cancellation can have even lower complexity than the linear MMSE detector. Moreover, our BLAST algorithm is also numerically stable and hardware friendly, since it uses unitary transformations to avoid the matrix inversions, and gets the initial square-root which is equivalent to a Cholesky factor of the estimation error covariance matrix.