Enhanced Trellis Coded Multiple Access (ETCMA)

We propose an enhanced version of trellis coded multiple access (TCMA), an overloaded multiple access scheme that outperforms the original TCMA in terms of achieved spectral efficiency. Enhanced TCMA (ETCMA) performs simultaneous transmission of multiple data streams intended for users experiencing similar signal-to-noise ratios and can be employed both in the uplink and in the downlink of wireless systems, thus overcoming one of the main limitations of TCMA. Thanks to a new receiver algorithm, ETCMA is capable of delivering a significantly higher spectral efficiency. We show that ETCMA approaches the capacity of the Additive White Gaussian Noise channel for a wide range of signal-to-noise ratios.Comment: 5 pages, 5 figure

High Capacity CDMA and Collaborative Techniques

The thesis investigates new approaches to increase the user capacity and improve the error performance of Code Division Multiple Access (CDMA) by employing adaptive interference cancellation and collaborative spreading and space diversity techniques. Collaborative Coding Multiple Access (CCMA) is also investigated as a separate technique and combined with CDMA. The advantages and shortcomings of CDMA and CCMA are analysed and new techniques for both the uplink and downlink are proposed and evaluated. Multiple access interference (MAI) problem in the uplink of CDMA is investigated first. The practical issues of multiuser detection (MUD) techniques are reviewed and a novel blind adaptive approach to interference cancellation (IC) is proposed. It exploits the constant modulus (CM) property of digital signals to blindly suppress interference during the despreading process and obtain amplitude estimation with minimum mean squared error for use in cancellation stages. Two new blind adaptive receiver designs employing successive and parallel interference cancellation architectures using the CM algorithm (CMA) referred to as ‘CMA-SIC’ and ‘BA-PIC’, respectively, are presented. These techniques have shown to offer near single user performance for large number of users. It is shown to increase the user capacity by approximately two fold compared with conventional IC receivers. The spectral efficiency analysis of the techniques based on output signal-to interference-and-noise ratio (SINR) also shows significant gain in data rate. Furthermore, an effective and low complexity blind adaptive subcarrier combining (BASC) technique using a simple gradient descent based algorithm is proposed for Multicarrier-CDMA. It suppresses MAI without any knowledge of channel amplitudes and allows large number of users compared with equal gain and maximum ratio combining techniques normally used in practice. New user collaborative schemes are proposed and analysed theoretically and by simulations in different channel conditions to achieve spatial diversity for uplink of CCMA and CDMA. First, a simple transmitter diversity and its equivalent user collaborative diversity techniques for CCMA are designed and analysed. Next, a new user collaborative scheme with successive interference cancellation for uplink of CDMA referred to as collaborative SIC (C-SIC) is investigated to reduce MAI and achieve improved diversity. To further improve the performance of C-SIC under high system loading conditions, Collaborative Blind Adaptive SIC (C-BASIC) scheme is proposed. It is shown to minimize the residual MAI, leading to improved user capacity and a more robust system. It is known that collaborative diversity schemes incur loss in throughput due to the need of orthogonal time/frequency slots for relaying source’s data. To address this problem, finally a novel near-unity-rate scheme also referred to as bandwidth efficient collaborative diversity (BECD) is proposed and evaluated for CDMA. Under this scheme, pairs of users share a single spreading sequence to exchange and forward their data employing a simple superposition or space-time encoding methods. At the receiver collaborative joint detection is performed to separate each paired users’ data. It is shown that the scheme can achieve full diversity gain at no extra bandwidth as inter-user channel SNR becomes high. A novel approach of ‘User Collaboration’ is introduced to increase the user capacity of CDMA for both the downlink and uplink. First, collaborative group spreading technique for the downlink of overloaded CDMA system is introduced. It allows the sharing of the same single spreading sequence for more than one user belonging to the same group. This technique is referred to as Collaborative Spreading CDMA downlink (CS-CDMA-DL). In this technique T-user collaborative coding is used for each group to form a composite codeword signal of the users and then a single orthogonal sequence is used for the group. At each user’s receiver, decoding of composite codeword is carried out to extract the user’s own information while maintaining a high SINR performance. To improve the bit error performance of CS-CDMA-DL in Rayleigh fading conditions, Collaborative Space-time Spreading (C-STS) technique is proposed by combining the collaborative coding multiple access and space-time coding principles. A new scheme for uplink of CDMA using the ‘User Collaboration’ approach, referred to as CS-CDMA-UL is presented next. When users’ channels are independent (uncorrelated), significantly higher user capacity can be achieved by grouping multiple users to share the same spreading sequence and performing MUD on per group basis followed by a low complexity ML decoding at the receiver. This approach has shown to support much higher number of users than the available sequences while also maintaining the low receiver complexity. For improved performance under highly correlated channel conditions, T-user collaborative coding is also investigated within the CS-CDMA-UL system

Sub-graph based joint sparse graph for sparse code multiple access systems

Sparse code multiple access (SCMA) is a promising air interface candidate technique for next generation mobile networks, especially for massive machine type communications (mMTC). In this paper, we design a LDPC coded SCMA detector by combining the sparse graphs of LDPC and SCMA into one joint sparse graph (JSG). In our proposed scheme, SCMA sparse graph (SSG) defined by small size indicator matrix is utilized to construct the JSG, which is termed as sub-graph based joint sparse graph of SCMA (SG-JSG-SCMA). In this paper, we first study the binary-LDPC (B-LDPC) coded SGJSG- SCMA system. To combine the SCMA variable node (SVN) and LDPC variable node (LVN) into one joint variable node (JVN), a non-binary LDPC (NB-LDPC) coded SG-JSG-SCMA is also proposed. Furthermore, to reduce the complexity of NBLDPC coded SG-JSG-SCMA, a joint trellis representation (JTR) is introduced to represent the search space of NB-LDPC coded SG-JSG-SCMA. Based on JTR, a low complexity joint trellis based detection and decoding (JTDD) algorithm is proposed to reduce the computational complexity of NB-LDPC coded SGJSG- SCMA system. According to the simulation results, SG-JSGSCMA brings significant performance improvement compare to the conventional receiver using the disjoint approach, and it can also outperform a Turbo-structured receiver with comparable complexity. Moreover, the joint approach also has advantages in terms of processing latency compare to the Turbo approaches

Deep Learning-Aided Multicarrier Systems

This paper proposes a deep learning (DL)-aided multicarrier (MC) system operating on fading channels, where both modulation and demodulation blocks are modeled by deep neural networks (DNNs), regarded as the encoder and decoder of an autoencoder (AE) architecture, respectively. Unlike existing AE-based systems, which incorporate domain knowledge of a channel equalizer to suppress the effects of wireless channels, the proposed scheme, termed as MC-AE, directly feeds the decoder with the channel state information and received signal, which are then processed in a fully data-driven manner. This new approach enables MC-AE to jointly learn the encoder and decoder to optimize the diversity and coding gains over fading channels. In particular, the block error rate of MC-AE is analyzed to show its higher performance gains than existing hand-crafted baselines, such as various recent index modulation-based MC schemes. We then extend MC-AE to multiuser scenarios, wherein the resultant system is termed as MU-MC-AE. Accordingly, two novel DNN structures for uplink and downlink MU-MC-AE transmissions are proposed, along with a novel cost function that ensures a fast training convergence and fairness among users. Finally, simulation results are provided to show the superiority of the proposed DL-based schemes over current baselines, in terms of both the error performance and receiver complexity

Hybrid generalized non-orthogonal multiple access for the 5G wireless networks.

Master of Science in Computer Engineering. University of KwaZulu-Natal. Durban, 2018.The deployment of 5G networks will lead to an increase in capacity, spectral efficiency, low latency and massive connectivity for wireless networks. They will still face the challenges of resource and power optimization, increasing spectrum efficiency and energy optimization, among others. Furthermore, the standardized technologies to mitigate against the challenges need to be developed and are a challenge themselves. In the current predecessor LTE-A networks, orthogonal frequency multiple access (OFDMA) scheme is used as the baseline multiple access scheme. It allows users to be served orthogonally in either time or frequency to alleviate narrowband interference and impulse noise. Further spectrum limitations of orthogonal multiple access (OMA) schemes have resulted in the development of non-orthogonal multiple access (NOMA) schemes to enable 5G networks to achieve high spectral efficiency and high data rates. NOMA schemes unorthogonally co-multiplex different users on the same resource elements (RE) (i.e. time-frequency domain, OFDMA subcarrier, or spreading code) via power domain (PD) or code domain (CD) at the transmitter and successfully separating them at the receiver by applying multi-user detection (MUD) algorithms. The current developed NOMA schemes, refered to as generalized-NOMA (G-NOMA) technologies includes; Interleaver Division Multiple Access (IDMA, Sparse code multiple access (SCMA), Low-density spreading multiple access (LDSMA), Multi-user shared access (MUSA) scheme and the Pattern Division Multiple Access (PDMA). These protocols are currently still under refinement, their performance and applicability has not been thoroughly investigated. The first part of this work undertakes a thorough investigation and analysis of the performance of the existing G-NOMA schemes and their applicability. Generally, G-NOMA schemes perceives overloading by non-orthogonal spectrum resource allocation, which enables massive connectivity of users and devices, and offers improved system spectral efficiency. Like any other technologies, the G-NOMA schemes need to be improved to further harvest their benefits on 5G networks leading to the requirement of Hybrid G-NOMA (G-NOMA) schemes. The second part of this work develops a HG-NOMA scheme to alleviate the 5G challenges of resource allocation, inter and cross-tier interference management and energy efficiency. This work develops and investigates the performance of an Energy Efficient HG-NOMA resource allocation scheme for a two-tier heterogeneous network that alleviates the cross-tier interference and improves the system throughput via spectrum resource optimization. By considering the combinatorial problem of resource pattern assignment and power allocation, the HG-NOMA scheme will enable a new transmission policy that allows more than two macro-user equipment’s (MUEs) and femto-user equipment’s (FUEs) to be co-multiplexed on the same time-frequency RE increasing the spectral efficiency. The performance of the developed model is shown to be superior to the PD-NOMA and OFDMA schemes