66 research outputs found

    Rate-splitting multiple access for non-terrestrial communication and sensing networks

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    Rate-splitting multiple access (RSMA) has emerged as a powerful and flexible non-orthogonal transmission, multiple access (MA) and interference management scheme for future wireless networks. This thesis is concerned with the application of RSMA to non-terrestrial communication and sensing networks. Various scenarios and algorithms are presented and evaluated. First, we investigate a novel multigroup/multibeam multicast beamforming strategy based on RSMA in both terrestrial multigroup multicast and multibeam satellite systems with imperfect channel state information at the transmitter (CSIT). The max-min fairness (MMF)-degree of freedom (DoF) of RSMA is derived and shown to provide gains compared with the conventional strategy. The MMF beamforming optimization problem is formulated and solved using the weighted minimum mean square error (WMMSE) algorithm. Physical layer design and link-level simulations are also investigated. RSMA is demonstrated to be very promising for multigroup multicast and multibeam satellite systems taking into account CSIT uncertainty and practical challenges in multibeam satellite systems. Next, we extend the scope of research from multibeam satellite systems to satellite- terrestrial integrated networks (STINs). Two RSMA-based STIN schemes are investigated, namely the coordinated scheme relying on CSI sharing and the co- operative scheme relying on CSI and data sharing. Joint beamforming algorithms are proposed based on the successive convex approximation (SCA) approach to optimize the beamforming to achieve MMF amongst all users. The effectiveness and robustness of the proposed RSMA schemes for STINs are demonstrated. Finally, we consider RSMA for a multi-antenna integrated sensing and communications (ISAC) system, which simultaneously serves multiple communication users and estimates the parameters of a moving target. Simulation results demonstrate that RSMA is beneficial to both terrestrial and multibeam satellite ISAC systems by evaluating the trade-off between communication MMF rate and sensing Cramer-Rao bound (CRB).Open Acces

    Multiuser MIMO-OFDM for Next-Generation Wireless Systems

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    This overview portrays the 40-year evolution of orthogonal frequency division multiplexing (OFDM) research. The amelioration of powerful multicarrier OFDM arrangements with multiple-input multiple-output (MIMO) systems has numerous benefits, which are detailed in this treatise. We continue by highlighting the limitations of conventional detection and channel estimation techniques designed for multiuser MIMO OFDM systems in the so-called rank-deficient scenarios, where the number of users supported or the number of transmit antennas employed exceeds the number of receiver antennas. This is often encountered in practice, unless we limit the number of users granted access in the base station’s or radio port’s coverage area. Following a historical perspective on the associated design problems and their state-of-the-art solutions, the second half of this treatise details a range of classic multiuser detectors (MUDs) designed for MIMO-OFDM systems and characterizes their achievable performance. A further section aims for identifying novel cutting-edge genetic algorithm (GA)-aided detector solutions, which have found numerous applications in wireless communications in recent years. In an effort to stimulate the cross pollination of ideas across the machine learning, optimization, signal processing, and wireless communications research communities, we will review the broadly applicable principles of various GA-assisted optimization techniques, which were recently proposed also for employment inmultiuser MIMO OFDM. In order to stimulate new research, we demonstrate that the family of GA-aided MUDs is capable of achieving a near-optimum performance at the cost of a significantly lower computational complexity than that imposed by their optimum maximum-likelihood (ML) MUD aided counterparts. The paper is concluded by outlining a range of future research options that may find their way into next-generation wireless systems

    Low complexity detection for SC-FDE massive MIMO systems

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    Nowadays we continue to observe a big and fast growth of wireless com-munication usage due to the increasing number of access points, and fields of application of this technology. Furthermore, these new usages can require higher speed and better quality of service in order to create market. As example we can have: live 4K video transmission, M2M (Machine to Machine communication), IoT (Internet of Things), Tactile Internet, between many others. As a consequence of all these factors, the spectrum is getting overloaded with communications, increasing the interference and affecting the system's per-formance. Therefore a different path of ideas has been followed and the commu-nication process has been taken to the next level in 5G by the usage of big arrays of antennas and multi-stream communication (MIMO systems) which in a greater scale are called massive MIMO schemes. These systems can be combined with an SC-FDE (Single-Carrier Frequency Domain Equalization) scheme to im-prove the power efficiency due to the low envelope fluctuations. This thesis focused on the equalization in massive MIMO systems, more specifically in the FDE (Frequency Domain Equalization), studying the perfor-mance of different approaches, namely ZF (Zero Forcing), EGD (Equal Gain De-tector), MRD (Maximum Ratio Detector), IB-DFE (Iterative Block Decision Feed-back Equalizer) and a proposed receiver combining MRD (or EGD) and IB-DFE.With this approach we want to minimize the ICI (Inter Carrier Interference) in order to have almost independent data streams and to produce a low complexity code, so that the receiver's performance doesn't affect the total system's perfor-mance, with a final objective of increasing the data throughput in a great scale

    Efficient Radio Resource Allocation Schemes and Code Optimizations for High Speed Downlink Packet Access Transmission

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    An important enhancement on the Wideband Code Division Multiple Access (WCDMA) air interface of the 3G mobile communications, High Speed Downlink Packet Access (HSDPA) standard has been launched to realize higher spectral utilization efficiency. It introduces the features of multicode CDMA transmission and Adaptive Modulation and Coding (AMC) technique, which makes radio resource allocation feasible and essential. This thesis studies channel-aware resource allocation schemes, coupled with fast power adjustment and spreading code optimization techniques, for the HSDPA standard operating over frequency selective channel. A two-group resource allocation scheme is developed in order to achieve a promising balance between performance enhancement and time efficiency. It only requires calculating two parameters to specify the allocations of discrete bit rates and transmitted symbol energies in all channels. The thesis develops the calculation methods of the two parameters for interference-free and interference-present channels, respectively. For the interference-present channels, the performance of two-group allocation can be further enhanced by applying a clustering-based channel removal scheme. In order to make the two-group approach more time-efficient, reduction in matrix inversions in optimum energy calculation is then discussed. When the Minimum Mean Square Error (MMSE) equalizer is applied, optimum energy allocation can be calculated by iterating a set of eigenvalues and eigenvectors. By using the MMSE Successive Interference Cancellation (SIC) receiver, the optimum energies are calculated recursively combined with an optimum channel ordering scheme for enhancement in both system performance and time efficiency. This thesis then studies the signature optimization methods with multipath channel and examines their system performances when combined with different resource allocation methods. Two multipath-aware signature optimization methods are developed by applying iterative optimization techniques, for the system using MMSE equalizer and MMSE precoder respectively. A PAM system using complex signature sequences is also examined for improving resource utilization efficiency, where two receiving schemes are proposed to fully take advantage of PAM features. In addition by applying a short chip sampling window, a Singular Value Decomposition (SVD) based interference-free signature design method is presented

    Signal Processing Techniques for 6G

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    Optimizing Communication Beamforming for New Multiple Access under Low-Resolution Quantization: A Spectral and Energy Efficiency Perspective

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    Department of Electrical EngineeringCurrently, there is growing interest in 6G wireless communication beyond the era of 5G. In addition, the hardware devices require high-speed wireless communication and low-power communications. For example, there are applications such as the internet-of-things (IoT), where devices are limited by battery capacity and have low computing capabilities but require high spectral efficiency. In order to address the issue of power consumption in wireless communication, low-power hardware such as low-resolution analog-to-digital converter (ADC) and digital-to-analog converter (DAC) systems are having attention as a promising transceiver architecture. This is because the power consumption of quantizers decreases exponentially as the number of quantization bits decreases. In this dissertation, low-resolution quantizer system is considered to achieve the trade-off between high spectral efficiency and energy efficiency. Another challenge that needs to be addressed in the development of 6G wireless communications is the severe inter-user interference resulting from the exponential increase in the number of smart devices. For example, in IoT communications, the large number of IoT devices and high channel correlation among them can lead to a significant amount of inter-user interference, which in turn can cause considerable degradation in spectral performance. In this regard, new multiple access approaches are introduced such as rate-splitting multiple access (RSMA), non-orthogonal multiple access (NOMA), spatial-division multiple access (SDMA), and orthogonal multiple access (OMA) to control the interuser interference. Specifically, I consider rate-splitting multiple access to boost the spectral efficiency because rate-splitting multiple access provides extra achievable antenna degree-of freedom by dividing the messages into common and private messages. It is difficult to optimize rate-splitting multiple access precoders due to the minimum rate constraint involved in determining the common rate. Furthermore, the designing quantized precoders is more highly challenging to solve the optimization problem. In this dissertation, I develop a promising RSMA precoder algorithm coupled with quantization errors to maximize the spectral efficiency. To make the optimization problem in smooth function, I first approximate the spectral efficiency of common stream utilizing the Log-Sum Exp technique. Then, I derive the first-order optimality condition in terms of the nonlinear eigenvalue problem (NEP). I suggest computationally efficient method to find a sub-optimal solution for obtaining the principal eigen-vector of the nonlinear eigenvalue problem. In addition, I propose the weighted minimum mean square error-based RSMA precoding algorithm to the considered quantization system. Simulation results demonstrate the performance of the proposed algorithm in terms of the spectral efficiency, and more importantly, ratesplitting multiple access can achieve key benefit than spatial-division multiple access by balancing between the channel gain and quantization error utilizing the common stream in multiuser MIMO systems.clos

    Optimization techniques for reliable data communication in multi-antenna wireless systems

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    This thesis looks at new methods of achieving reliable data communication in wireless communication systems using different antenna transmission optimization methods. In particular, the problems of exploitation of MIMO communication channel diversity, secure downlink beamforming techniques, adaptive beamforming techniques, resource allocation methods, simultaneous power and information transfer and energy harvesting within the context of multi-antenna wireless systems are addressed

    High capacity multiuser multiantenna communication techniques

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    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
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