An interference-reducing precoding for SCMA multicast design based on complementary sequences

In a multi-group multicast sparse code multiple access (SCMA) system, one base station multicasts common messages to multiple multicast groups via different code books. To accommodate more user terminals (UTs), traditional multicast systems have multiple transmitters, each of which works in one-to-many mode. In this way, each UT is subject to inter-transmitter interference. Considering the high degrees of freedom for transmitting and receiving, it is difficult to separate the desired signal from interference signals. Therefore, an interference-reducing precoding scheme is required to ensure the reliability of SCMA multicast communication system. For the SCMA multicast system design, we present three necessary conditions that the interference-reducing matrix should satisfy. Then, the precoding matrix satisfying the three necessary conditions simultaneously is designed by utilizing the complementary sequences (CS) and complete complementary sequences (CCS). In this context, we consider two scenarios with different transmission modes (single-cell and multiple-cell) and different precoding schemes (based on CS and CCS). Simulation results show that proposed transmission schemes can significantly reduce the bit error rate of multicast groups while ensuring the communication throughput, and behave a superior performance over other alternatives. Moreover, theoretical and simulation results also prove that the proposed precoding vectors have perfect average power radiation and omnidirectional coverage performance

Compressive Sensing-Based Grant-Free Massive Access for 6G Massive Communication

The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires advanced system capabilities far beyond existing network architectures. In particular, such massive communication has been recognized as a prime driver that can empower the 6G vision of future ubiquitous connectivity, supporting Internet of Human-Machine-Things for which massive access is critical. This paper surveys the most recent advances toward massive access in both academic and industry communities, focusing primarily on the promising compressive sensing-based grant-free massive access paradigm. We first specify the limitations of existing random access schemes and reveal that the practical implementation of massive communication relies on a dramatically different random access paradigm from the current ones mainly designed for human-centric communications. Then, a compressive sensing-based grant-free massive access roadmap is presented, where the evolutions from single-antenna to large-scale antenna array-based base stations, from single-station to cooperative massive multiple-input multiple-output systems, and from unsourced to sourced random access scenarios are detailed. Finally, we discuss the key challenges and open issues to shed light on the potential future research directions of grant-free massive access.Comment: Accepted by IEEE IoT Journa

Signal Processing and Learning for Next Generation Multiple Access in 6G

Wireless communication systems to date primarily rely on the orthogonality of resources to facilitate the design and implementation, from user access to data transmission. Emerging applications and scenarios in the sixth generation (6G) wireless systems will require massive connectivity and transmission of a deluge of data, which calls for more flexibility in the design concept that goes beyond orthogonality. Furthermore, recent advances in signal processing and learning have attracted considerable attention, as they provide promising approaches to various complex and previously intractable problems of signal processing in many fields. This article provides an overview of research efforts to date in the field of signal processing and learning for next-generation multiple access, with an emphasis on massive random access and non-orthogonal multiple access. The promising interplay with new technologies and the challenges in learning-based NGMA are discussed

Nonorthogonal Multiple Access for 5G and Beyond

This work was supported in part by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/N029720/1 and Grant EP/N029720/2. The work of L. Hanzo was supported by the ERC Advanced Fellow Grant Beam-me-up

Resource allocation in non-orthogonal multiple access technologies for 5G networks and beyond.

Doctoral Degree. University of KwaZulu-Natal, Durban.The increasing demand of mobile and device connectivity poses challenging requirements for 5G wireless communications, such as high energy- and spectral-efficiency and low latency. This necessitates a shift from orthogonal multiple access (OMA) to Non-Orthogonal Multiple Access (NOMA) techniques, namely, power-domain NOMA (PD-NOMA) and code-domain NOMA (CD-NOMA). The basic idea behind NOMA schemes is to co-multiplex different users on the same resource elements (time slot, OFDMA sub-carrier, or spreading code) via power domain (PD) or code domain (CD) at the transmitter while permitting controllable interference, and their successful multi-user detection (MUD) at the receiver albeit, increased computational complexity. In this work, an analysis on the performance of the existing NOMA schemes is carried out. Furthermore, we investigate the feasibility of a proposed uplink hybrid-NOMA scheme namely power domain sparse code multiple access (PD-SCMA) that integrates PD-NOMA and CD-NOMA based sparse code multiple access (SCMA) on heterogeneous networks (HetNets). Such hybrid schemes come with resource allocation (RA) challenges namely; codebook allocation, user pairing and power allocation. Therefore, hybrid RA schemes namely: Successive Codebook Ordering Assignment (SCOA) for codebook assignment (CA), opportunistic macro cell user equipment (MUE)- small cell user equipment (SUE) pairing (OMSP) for user pairing (UP), and a QoS-aware power allocation (QAPA) for power allocation (PA) are developed for an energy efficient (EE) system. The performance of the RA schemes is analyzed alongside an analytical RA optimization algorithm. Through numerical results, the proposed schemes show significant improvements in the EE of the small cells in comparison with the prevalent schemes. Additionally, there is significant sum rate performance improvement over the conventional SCMA and PD-NOMA. Secondly, we investigate the multiplexing capacity of the hybrid PD-SCMA scheme in HetNets. Particularly, we investigate and derive closed-form solutions for codebook capacity, MUE multiplexing and power capacity bounds. The system’s performance results into low outage when the system’s point of operation is within the multiplexing bounds. To alleviate the RA challenges of such a system at the transmitter, dual parameter ranking (DPR) and alternate search method (ASM) based RA schemes are proposed. The results show significant capacity gain with DPR-RA in comparison with conventional RA schemes. Lastly, we investigate the feasibility of integrating the hybrid PD-SCMA with multiple-input multipleoutput (MIMO) technique namely, M-PD-SCMA. The attention to M-PD-SCMA resides in the need of lower number of antennas while preserving the system capacity thanks to the overload in PDSCMA. To enhance spectral efficiency and error performance we propose spatial multiplexing at the transmitter and a low complex joint MUD scheme based on successive interference cancellation (SIC) and expectation propagation algorithm (EPA) at the receiver are proposed. Numerical results exhibit performance benchmark with PD-SCMA schemes and the proposed receiver achieves guaranteed bit error rate (BER) performance with a bounded increase in the number of transmit and receive antennas. Thus, the feasibility of an M-PD-SCMA system is validated

Advanced digital signal processing for next-generation flexible optical networks

To keep pace with the rapid expansion in data-exchange traffic around the world, optical networks are anticipated to provide flexibility to maximize utilization of the deployed optical fiber resources. On the other hand, digital signal processing (DSP) has been employed in coherent optical systems to enable 100G and beyond optical fiber networks. The goal of the thesis is to develop advanced DSP techniques for the flexible optical networks. With the reconfigured modulation formats in the systems, modulation classification (MC) is essential in the DSP to facilitate the sequential compensation modules which are modulation format-dependent. Based on the cumulative distribution function (CDF) of received signal's amplitude, an MC algorithm for M-ary quadrature amplitude modulation (M-QAM) formats with M = 4, 8, 16, 32, and 64 is proposed. Results show that the proposed algorithm achieves accurate classification at optical signal-to-noise ratio (OSNR) of interest and is robust to frequency offset and laser phase noise. Relying on the CDF of received signal's amplitude, a non-data-aided (NDA) OSNR estimation algorithm is developed for coherent optical systems employing multilevel constellations. It outperforms the state-of-the-art NDA algorithm in terms of performance and complexity. Furthermore, a joint OSNR estimation and MC algorithm enabled by support vector machine is designed. Compared to deep neural network-based joint estimation approach, the proposed algorithm achieves better performance with comparable complexity. In addition, a low-complexity two-stage carrier phase estimation algorithm is proposed for coherent optical systems with 16-QAM format. The proposed algorithm exploits the second power operation instead of the conventional fourth power to remove the modulation phase, which is enabled by constellation partition and rotation. Optical back-to-back experiments and numerical simulations are carried out to evaluate the performance of the algorithm. Results show that, compared with the conventional fourth power-based CPE algorithm, the proposed algorithm provides comparable tolerance to the carrier phase noise, with reduced complexity. Lastly, a novel transmission scheme is investigated for the open and disaggregated metro coherent optical networks, which impose the requirements for multiple user connectivities on the limited orthogonal frequency resources. Thus, it is desirable to provide connections simultaneously to various users in a non-orthogonal way. A transmission scheme based on the non-orthogonal sparse code multiple access in a digital subcarrier multiplexing is proposed. Compared to power domain-based counterpart, the proposed scheme supports more than 2 users without user pairing and clustering. The feasibility of the proposed scheme is verified through numerical simulations. Three scenarios with 2, 4, and 6 users over 1, 2, and 4 subcarriers, respectively, are considered. Performance evaluations show that in all scenarios, the proposed scheme attains bit error ratio lower than the forward error correction limits with the transmission ranges of interest in metro applications