Quantum-aided multi-user transmission in non-orthogonal multiple access systems

With the research on implementing a universal quantum computer being under the technological spotlight, new possibilities appear for their employment in wireless communications systems for reducing their complexity and improving their performance. In this treatise, we consider the downlink of a rank-deficient, multi-user system and we propose the discrete-valued and continuous-valued Quantum-assisted Particle Swarm Optimization (QPSO) algorithms for performing Vector Perturbation (VP) precoding, as well as for lowering the required transmission power at the Base Station (BS), while minimizing the expected average Bit Error Ratio (BER) at the mobile terminals. We use the Minimum BER (MBER) criterion. We show that the novel quantum-assisted precoding methodology results in an enhanced BER performance, when compared to that of a classical methodology employing the PSO algorithm, while requiring the same computational complexity in the challenging rank-deficient scenarios, where the number of transmit antenna elements at the BS is lower than the number of users. Moreover, when there is limited Channel State Information (CSI) feedback from the users to the BS, due to the necessary quantization of the channel states, the proposed quantum-assisted precoder outperforms the classical precoder

Bit Loading and Peak Average Power Reduction Techniques for Adaptive Orthogonal Frequency Division Multiplexing Systems

In a frequency-selective channel a large number of resolvable multipaths are present which lead to the fading of the signal. Orthogonal frequency division multiplexing (OFDM) is well-known to be effective against multipath distortion. It is a multicarrier communication scheme, in which the bandwidth of the channel is divided into subcarriers and data symbols are modulated and transmitted on each subcarrier simultaneously. By inserting guard time that is longer than the delay spread of the channel, an OFDM system is able to mitigate intersymbol interference (ISI). Significant improvement in performance is achieved by adaptively loading the bits on the subcarriers based on the channel state information from the receiver. Imperfect channel state information (CSI) arises from noise at the receiver and also due to the time delay in providing the information to the transmitter for the next data transmission. This thesis presents an investigation into the different adaptive techniques for loading the data bits on the subcarriers. The choice of the loading technique is application specific. The spectral efficiency and the bit error rate (BER) performance of adaptive OFDM as well as the implementation complexity of the different loading algorithms is studied by varying any one of the parameters, data rate or BER or total transmit power subject to the constraints on the other two. A novel bit loading algorithm based on comparing the SNR with the threshold in order to minimize the BER is proposed and its performance for different data rates is plotted. Finally, this thesis presents a method for reducing the large peak to average power ratio (PAPR) problem with OFDM which arises when the sinusoidal signals of the subcarriers add constructively. The clipping and the probabilistic approaches were studied. The probabilistic technique shows comparatively better BER performance as well as reduced PAPR ratio but is more complex to implement

Studies on efficient spectrum sharing in coexisting wireless networks.

Wireless communication is facing serious challenges worldwide: the severe spectrum shortage along with the explosive increase of the wireless communication demands. Moreover, different communication networks may coexist in the same geographical area. By allowing multiple communication networks cooperatively or opportunistically sharing the same frequency will potentially enhance the spectrum efficiency. This dissertation aims to investigate important spectrum sharing schemes for coexisting networks. For coexisting networks operating in interweave cognitive radio mode, most existing works focus on the secondary network’s spectrum sensing and accessing schemes. However, the primary network can be selfish and tends to use up all the frequency resource. In this dissertation, a novel optimization scheme is proposed to let primary network maximally release unnecessary frequency resource for secondary networks. The optimization problems are formulated for both uplink and downlink orthogonal frequency-division multiple access (OFDMA)-based primary networks, and near optimal algorithms are proposed as well. For coexisting networks in the underlay cognitive radio mode, this work focuses on the resource allocation in distributed secondary networks as long as the primary network’s rate constraint can be met. Global optimal multicarrier discrete distributed (MCDD) algorithm and suboptimal Gibbs sampler based Lagrangian algorithm (GSLA) are proposed to solve the problem distributively. Regarding to the dirty paper coding (DPC)-based system where multiple networks share the common transmitter, this dissertation focuses on its fundamental performance analysis from information theoretic point of view. Time division multiple access (TDMA) as an orthogonal frequency sharing scheme is also investigated for comparison purpose. Specifically, the delay sensitive quality of service (QoS) requirements are incorporated by considering effective capacity in fast fading and outage capacity in slow fading. The performance metrics in low signal to noise ratio (SNR) regime and high SNR regime are obtained in closed forms followed by the detailed performance analysis

Robust transmit beamforming design using outage probability specification

Transmit beamforming (precoding) is a powerful technique for enhancing the channel capacity and reliability of multiple-input and multiple-output (MIMO) wireless systems. The optimum exploitation of the benefits provided by MIMO systems can be achieved when a perfect channel state information at transmitter (CSIT) is available. In practices, however, the channel knowledge is generally imperfect at transmitter because of the inevitable errors induced by finite feedback channel capacity, quantization and other physical constraints. Such errors degrade the system performance severely. Hence, robustness has become a crucial issue. Current robust designs address the channel imperfections with the worst-case and stochastic approaches. In worst-case analysis, the channel uncertainties are considered as deterministic and norm-bounded, and the resulting design is a conservative optimization that guarantees a certain quality of service (QoS) for every allowable perturbation. The latter approach focuses on the average performance under the assumption of channel statistics, such as mean and covariance. The system performance could break down when persistent extreme errors occur. Thus, an outage probability-based approach is developed by keeping a low probability that channel condition falls below an acceptable level. Compared to the aforementioned methods, this approach can optimize the average performance as well as consider the extreme scenarios proportionally. This thesis implements the outage-probability specification into transmit beamforming design for three scenarios: the single-user MIMO system and the corresponding adaptive modulation scheme as well as the multi-user MIMO system. In a single-user MIMO system, the transmit beamformer provides the maximum average received SNR and ensures the robustness to the CSIT errors by introducing probabilistic constraint on the instantaneous SNR. Beside the robustness against channel imperfections, the outage probability-based approach also provides a tight BER bound for adaptive modulation scheme, so that the maximum transmission rate can be achieved by taking advantage of transmit beamforming. Moreover, in multi-user MIMO (MU-MIMO) systems, the leakage power is accounted by probability measurement. The resulting transmit beamformer is designed based on signal-to-leakage-plus-noise ratio (SLNR) criteria, which maximizes the average received SNR and guarantees the least leakage energy from the desired user. In such a setting, an outstanding BER performance can be achieved as well as high reliability of signal-to-interference-plus-noise ratio (SINR). Given the superior overall performances and significantly improved robustness, the probabilistic approach provides an attractive alternative to existing robust techniques under imperfect channel information at transmitter

A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

IEEE Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area