High capacity multiuser multiantenna communication techniques

One of the main issues involved in the development of future wireless communication systems is the multiple access technique used to efficiently share the available spectrum among users. In rich multipath environment, spatial dimension can be exploited to meet the increasing number of users and their demands without consuming extra bandwidth and power. Therefore, it is utilized in the multiple-input multiple-output (MIMO) technology to increase the spectral efficiency significantly. However, multiuser MIMO (MU-MIMO) systems are still challenging to be widely adopted in next generation standards. In this thesis, new techniques are proposed to increase the channel and user capacity and improve the error performance of MU-MIMO over Rayleigh fading channel environment. For realistic system design and performance evaluation, channel correlation is considered as one of the main channel impurities due its severe influence on capacity and reliability. Two simple methods called generalized successive coloring technique (GSCT) and generalized iterative coloring technique (GICT) are proposed for accurate generation of correlated Rayleigh fading channels (CRFC). They are designed to overcome the shortcomings of existing methods by avoiding factorization of desired covariance matrix of the Gaussian samples. The superiority of these techniques is demonstrated by extensive simulations of different practical system scenarios. To mitigate the effects of channel correlations, a novel constellation constrained MU-MIMO (CC-MU-MIMO) scheme is proposed using transmit signal design and maximum likelihood joint detection (MLJD) at the receiver. It is designed to maximize the channel capacity and error performance based on principles of maximizing the minimum Euclidean distance (dmin) of composite received signals. Two signal design methods named as unequal power allocation (UPA) and rotation constellation (RC) are utilized to resolve the detection ambiguity caused by correlation. Extensive analysis and simulations demonstrate the effectiveness of considered scheme compared with conventional MU-MIMO. Furthermore, significant gain in SNR is achieved particularly in moderate to high correlations which have direct impact to maintain high user capacity. A new efficient receive antenna selection (RAS) technique referred to as phase difference based selection (PDBS) is proposed for single and multiuser MIMO systems to maximize the capacity over CRFC. It utilizes the received signal constellation to select the subset of antennas with highest (dmin) constellations due to its direct impact on the capacity and BER performance. A low complexity algorithm is designed by employing the Euclidean norm of channel matrix rows with their corresponding phase differences. Capacity analysis and simulation results show that PDBS outperforms norm based selection (NBS) and near to optimal selection (OS) for all correlation and SNR values. This technique provides fast RAS to capture most of the gains promised by multiantenna systems over different channel conditions. Finally, novel group layered MU-MIMO (GL-MU-MIMO) scheme is introduced to exploit the available spectrum for higher user capacity with affordable complexity. It takes the advantages of spatial difference among users and power control at base station to increase the number of users beyond the available number of RF chains. It is achieved by dividing the users into two groups according to their received power, high power group (HPG) and low power group (LPG). Different configurations of low complexity group layered multiuser detection (GL-MUD) and group power allocation ratio (η) are utilized to provide a valuable tradeoff between complexity and overall system performance. Furthermore, RAS diversity is incorporated by using NBS and a new selection algorithm called HPG-PDBS to increase the channel capacity and enhance the error performance. Extensive analysis and simulations demonstrate the superiority of proposed scheme compared with conventional MU-MIMO. By using appropriate value of (η), it shows higher sum rate capacity and substantial increase in the user capacity up to two-fold at target BER and SNR values

Heterogeneous integration of optical wireless communications within next generation networks

Unprecedented traffic growth is expected in future wireless networks and new technologies will be needed to satisfy demand. Optical wireless (OW) communication offers vast unused spectrum and high area spectral efficiency. In this work, optical cells are envisioned as supplementary access points within heterogeneous RF/OW networks. These networks opportunistically offload traffic to optical cells while utilizing the RF cell for highly mobile devices and devices that lack a reliable OW connection. Visible light communication (VLC) is considered as a potential OW technology due to the increasing adoption of solid state lighting for indoor illumination. Results of this work focus on a full system view of RF/OW HetNets with three primary areas of analysis. First, the need for network densication beyond current RF small cell implementations is evaluated. A media independent model is developed and results are presented that provide motivation for the adoption of hyper dense small cells as complementary components within multi-tier networks. Next, the relationships between RF and OW constraints and link characterization parameters are evaluated in order to define methods for fair comparison when user-centric channel selection criteria are used. RF and OW noise and interference characterization techniques are compared and common OW characterization models are demonstrated to show errors in excess of 100x when dominant interferers are present. Finally, dynamic characteristics of hyper dense OW networks are investigated in order to optimize traffic distribution from a network-centric perspective. A Kalman Filter model is presented to predict device motion for improved channel selection and a novel OW range expansion technique is presented that dynamically alters coverage regions of OW cells by 50%. In addition to analytical results, the dissertation describes two tools that have been created for evaluation of RF/OW HetNets. A communication and lighting simulation toolkit has been developed for modeling and evaluation of environments with VLC-enabled luminaires. The toolkit enhances an iterative site based impulse response simulator model to utilize GPU acceleration and achieves 10x speedup over the previous model. A software defined testbed for OW has also been proposed and applied. The testbed implements a VLC link and a heterogeneous RF/VLC connection that demonstrates the RF/OW HetNet concept as proof of concept

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

Analysis and Design of Non-Orthogonal Multiple Access (NOMA) Techniques for Next Generation Wireless Communication Systems

The current surge in wireless connectivity, anticipated to amplify significantly in future wireless technologies, brings a new wave of users. Given the impracticality of an endlessly expanding bandwidth, there’s a pressing need for communication techniques that efficiently serve this burgeoning user base with limited resources. Multiple Access (MA) techniques, notably Orthogonal Multiple Access (OMA), have long addressed bandwidth constraints. However, with escalating user numbers, OMA’s orthogonality becomes limiting for emerging wireless technologies. Non-Orthogonal Multiple Access (NOMA), employing superposition coding, serves more users within the same bandwidth as OMA by allocating different power levels to users whose signals can then be detected using the gap between them, thus offering superior spectral efficiency and massive connectivity. This thesis examines the integration of NOMA techniques with cooperative relaying, EXtrinsic Information Transfer (EXIT) chart analysis, and deep learning for enhancing 6G and beyond communication systems. The adopted methodology aims to optimize the systems’ performance, spanning from bit-error rate (BER) versus signal to noise ratio (SNR) to overall system efficiency and data rates. The primary focus of this thesis is the investigation of the integration of NOMA with cooperative relaying, EXIT chart analysis, and deep learning techniques. In the cooperative relaying context, NOMA notably improved diversity gains, thereby proving the superiority of combining NOMA with cooperative relaying over just NOMA. With EXIT chart analysis, NOMA achieved low BER at mid-range SNR as well as achieved optimal user fairness in the power allocation stage. Additionally, employing a trained neural network enhanced signal detection for NOMA in the deep learning scenario, thereby producing a simpler signal detection for NOMA which addresses NOMAs’ complex receiver problem

Throughput Enhancement and Power Optimization in NOMA-based Multiuser Multicast Systems

In recent years, Non-Orthogonal Multiple Access (NOMA) has emerged as a promising technique for enhancing the capacity and throughput of wireless communication systems. This thesis investigates the potential of NOMA in improving the performance of multiuser multicast systems, focusing on multibeam satellite communication systems in the forward link, throughput enhancement, and power optimization. We propose a novel framework that combines a NOMA scheme with multibeam architecture and frequency reuse in multicast transmission. The proposed framework enhances system throughput by optimizing power allocation. First, we present a comprehensive review of the principles and techniques related to NOMA and multibeam multicast systems, highlighting their unique challenges and potential benefits. Next, we introduce our proposed framework in 4-color frequency reuse satellite systems. In 4-color frequency reuse, each user receives signals from other co-channel beams. However, the level of isolation is such that the interbeam interference can be treated as background noise without significant performance degradation. This means that there is no collaboration between beams, and each beam can be isolated from the rest. Therefore, NOMA is considered in single-beam multicast satellite communication systems. The optimum power allocation to maximize the minimum fairness rate and sum-rate is derived for a given user clustering in a single beam. Moreover, an optimum user clustering is derived, which improves the system throughput. Next, we investigate our proposed framework in full frequency reuse satellite systems under perfect channel state information at the transmitter (CSIT). The proposed framework integrates the NOMA scheme in multicast multibeam architecture. Linear precoding techniques, such as zero-forcing (ZF) and minimum mean square error (MMSE), are used to cancel interbeam interference while NOMA is applied on a beam basis. NOMA and linear precoding are adopted for the proposed framework in multicast transmission. A low-complexity user scheduling is proposed to deal with the trade-offs between optimum user scheduling for linear precoding and the NOMA scheme. Moreover, a low-complexity linear precoding in multicast transmission is proposed based on unicast linear precoding methods and a mapper which deals with the lack of spatial degrees of freedom. To improve the performance of linear precoding, we present three mappers, where the proposed singular-value-decomposition (SVD) mapper demonstrates the best performance. To improve system throughput, power allocation should be optimized. In this thesis, we consider two objective functions: max-min fairness rate (MMF) and sum-rate. This thesis introduces a technique for addressing the non-convex MMF optimization issue in the proposed framework by employing auxiliary variables to convert it into a semi-definite programming problem, which can then be resolved using linear programming solvers. This thesis also suggests an approach to tackle the non-convex sum-rate maximization goal function in MB-MC-NOMA systems by constructing Lagrangian multipliers concerning the constraints. By employing quadratic transformations on the sum-of-ratios, the problem is restructured within an iterative sum-rate power optimization algorithm. This thesis considers a realistic scenario with imperfect CSIT. To combat the effect of imperfect CSIT in multibeam multicast satellite communication systems, a rate-splitting approach is proposed. An averaging rate (AR) framework for MMF rate and sum-rate optimization considering ICST is proposed. To render the formulated MMF and sum-rate problems convex, we utilize the Weighted Minimum Mean Square Error (WMMSE) method. We first derive a rate-WMMSE relationship and then, using this relationship along with a low-complexity solution based on Alternating Optimization (AO), we transform the problems into equivalent convex ones. To validate the effectiveness of our proposed frameworks, we conduct extensive simulations and comparisons with state-of-the-art schemes. The results demonstrate significant improvements in throughput and power efficiency, confirming the potential of NOMA-based multiuser multicast systems for future wireless communication networks. Finally, we discuss potential future research directions, including the integration of the proposed frameworks in the cellular networks, calculating the transmitter and receiver complexity of the proposed techniques, considering higher layers of RS. This thesis contributes to the ongoing development of next-generation wireless communication systems, paving the way for more efficient and reliable data transmission in multiuser multicast environments

Collaborative modulation multiple access for single hop and multihop networks

While the bandwidth available for wireless networks is limited, the world has seen an unprecedented growth in the number of mobile subscribers and an ever increasing demand for high data rates. Therefore efficient utilisation of bandwidth to maximise link spectral efficiency and number of users that can be served simultaneously are primary goals in the design of wireless systems. To achieve these goals, in this thesis, a new non-orthogonal uplink multiple access scheme which combines the functionalities of adaptive modulation and multiple access called collaborative modulation multiple access (CMMA) is proposed. CMMA enables multiple users to access the network simultaneously and share the same bandwidth even when only a single receive antenna is available and in the presence of high channel correlation. Instead of competing for resources, users in CMMA share resources collaboratively by employing unique modulation sets (UMS) that differ in phase, power, and/or mapping structure. These UMS are designed to insure that the received signal formed from the superposition of all users’ signals belongs to a composite QAM constellation (CC) with a rate equal to the sum rate of all users. The CC and its constituent UMSs are designed centrally at the BS to remove ambiguity, maximize the minimum Euclidian distance (dmin) of the CC and insure a minimum BER performance is maintained. Users collaboratively precode their transmitted signal by performing truncated channel inversion and phase rotation using channel state information (CSI ) obtained from a periodic common pilot to insure that their combined signal at the BS belongs to the CC known at the BS which in turn performs a simple joint maximum likelihood detection without the need for CSI. The coherent addition of users’ power enables CMMA to achieve high link spectral efficiency at any time without extra power or bandwidth but on the expense of graceful degradation in BER performance. To improve the BER performance of CMMA while preserving its precoding and detection structure and without the need for pilot-aided channel estimation, a new selective diversity combining scheme called SC-CMMA is proposed. SC-CMMA optimises the overall group performance providing fairness and diversity gain for various users with different transmit powers and channel conditions by selecting a single antenna out of a group of L available antennas that minimises the total transmit power required for precoding at any one time. A detailed study of capacity and BER performance of CMMA and SC-CMMA is carried out under different level of channel correlations which shows that both offer high capacity gain and resilience to channel correlation. SC-CMMA capacity even increase with high channel correlation between users’ channels. CMMA provides a practical solution for implementing the multiple access adder channel (MAAC) in fading environments hence a hybrid approach combining both collaborative coding and modulation referred to as H-CMMA is investigated. H-CMMA divides users into a number of subgroups where users within a subgroup are assigned the same modulation set and different multiple access codes. H-CMMA adjusts the dmin of the received CC by varying the number of subgroups which in turn varies the number of unique constellation points for the same number of users and average total power. Therefore H-CMMA can accommodate many users with different rates while flexibly managing the complexity, rate and BER performance depending on the SNR. Next a new scheme combining CMMA with opportunistic scheduling using only partial CSI at the receiver called CMMA-OS is proposed to combine both the power gain of CMMA and the multiuser diversity gain that arises from users’ channel independence. To avoid the complexity and excessive feedback associated with the dynamic update of the CC, the BS takes into account the independence of users’ channels in the design of the CC and its constituent UMSs but both remain unchanged thereafter. However UMS are no longer associated with users, instead channel gain’s probability density function is divided into regions with identical probability and each UMS is associated with a specific region. This will simplify scheduling as users can initially chose their UMS based on their CSI and the BS will only need to resolve any collision when the channels of two or more users are located at the same region. Finally a high rate cooperative communication scheme, called cooperative modulation (CM) is proposed for cooperative multiuser systems. CM combines the reliability of the cooperative diversity with the high spectral efficiency and multiple access capabilities of CMMA. CM maintains low feedback and high spectral efficiency by restricting relaying to a single route with the best overall channel. Two possible variations of CM are proposed depending on whether CSI available only at the users or just at the BS and the selected relay. The first is referred to Precode, Amplify, and Forward (PAF) while the second one is called Decode, Remap, and Forward (DMF). A new route selection algorithm for DMF based on maximising dmin of random CC is also proposed using a novel fast low-complexity multi-stage sphere based algorithm to calculate the dmin at the relay of random CC that is used for both relay selection and detection

Enabling Efficient Communications Over Millimeter Wave Massive MIMO Channels Using Hybrid Beamforming

The use of massive multiple-input multiple-output (MIMO) over millimeter wave (mmWave) channels is the new frontier for fulfilling the exigent requirements of next-generation wireless systems and solving the wireless network impending crunch. Massive MIMO systems and mmWave channels offer larger numbers of antennas, higher carrier frequencies, and wider signaling bandwidths. Unleashing the full potentials of these tremendous degrees of freedom (dimensions) hinges on the practical deployment of those technologies. Hybrid analog and digital beamforming is considered as a stepping-stone to the practical deployment of mmWave massive MIMO systems since it significantly reduces their operating and implementation costs, energy consumption, and system design complexity. The prevalence of adopting mmWave and massive MIMO technologies in next-generation wireless systems necessitates developing agile and cost-efficient hybrid beamforming solutions that match the various use-cases of these systems. In this thesis, we propose hybrid precoding and combining solutions that are tailored to the needs of these specific cases and account for the main limitations of hybrid processing. The proposed solutions leverage the sparsity and spatial correlation of mmWave massive MIMO channels to reduce the feedback overhead and computational complexity of hybrid processing. Real-time use-cases of next-generation wireless communication, including connected cars, virtual-reality/augmented-reality, and high definition video transmission, require high-capacity and low-latency wireless transmission. On the physical layer level, this entails adopting near capacity-achieving transmission schemes with very low computational delay. Motivated by this, we propose low-complexity hybrid precoding and combining schemes for massive MIMO systems with partially and fully-connected antenna array structures. Leveraging the disparity in the dimensionality of the analog and the digital processing matrices, we develop a two-stage channel diagonalization design approach in order to reduce the computational complexity of the hybrid precoding and combining while maintaining high spectral efficiency. Particularly, the analog processing stage is designed to maximize the antenna array gain in order to avoid performing computationally intensive operations such as matrix inversion and singular value decomposition in high dimensions. On the other hand, the low-dimensional digital processing stage is designed to maximize the spectral efficiency of the systems. Computational complexity analysis shows that the proposed schemes offer significant savings compared to prior works where asymptotic computational complexity reductions ranging between $80\%$ and $98\%$. Simulation results validate that the spectral efficiency of the proposed schemes is near-optimal where in certain scenarios the signal-to-noise-ratio (SNR) gap to the optimal fully-digital spectral efficiency is less than $1$ dB. On the other hand, integrating mmWave and massive MIMO into the cellular use-cases requires adopting hybrid beamforming schemes that utilize limited channel state information at the transmitter (CSIT) in order to adapt the transmitted signals to the current channel. This is so mainly because obtaining perfect CSIT in frequency division duplexing (FDD) architecture, which dominates the cellular systems, poses serious concerns due to its large training and excessive feedback overhead. Motivated by this, we develop low-overhead hybrid precoding algorithms for selecting the baseband digital and radio frequency (RF) analog precoders from statistically skewed DFT-based codebooks. The proposed algorithms aim at maximizing the spectral efficiency based on minimizing the chordal distance between the optimal unconstrained precoder and the hybrid beamformer and maximizing the signal to interference noise ratio for the single-user and multi-user cases, respectively. Mathematical analysis shows that the proposed algorithms are asymptotically optimal as the number of transmit antennas goes to infinity and the mmWave channel has a limited number of paths. Moreover, it shows that the performance gap between the lower and upper bounds depends heavily on how many DFT columns are aligned to the largest eigenvectors of the transmit antenna array response of the mmWave channel or equivalently the transmit channel covariance matrix when only the statistical channel knowledge is available at the transmitter. Further, we verify the performance of the proposed algorithms numerically where the obtained results illustrate that the spectral efficiency of the proposed algorithms can approach that of the optimal precoder in certain scenarios. Furthermore, these results illustrate that the proposed hybrid precoding schemes have superior spectral efficiency performance while requiring lower (or at most comparable) channel feedback overhead in comparison with the prior art