115 research outputs found

    Closed-Form Sum-MSE Minimization for the Two-User Gaussian MIMO Broadcast Channel

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    Mathematical optimization and signal processing techniques for cooperative wireless networks

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    The rapid growth of mobile users and emergence of high data rate multimedia and interactive services have resulted in a shortage of the radio spectrum. Novel solutions are therefore required for future generations of wireless networks to enhance capacity and coverage. This thesis aims at addressing this issue through the design and analysis of signal processing algorithms. In particular various resource allocation and spatial diversity techniques have been proposed within the context of wireless peer-to-peer relays and coordinated base station (BS) processing. In order to enhance coverage while providing improvement in capacity, peer-to-peer relays that share the same frequency band have been considered and various techniques for designing relay coefficients and allocating powers optimally are proposed. Both one-way and two-way amplify and forward (AF) relays have been investigated. In order to maintain fairness, a signal-to-interference plus noise ratio (SINR) balancing criterion has been adopted. In order to improve the spectrum utilization further, the relays within the context of cognitive radio network are also considered. In this case, a cognitive peer-to-peer relay network is required to achieve SINR balancing while maintaining the interference leakage to primary receiver below a certain threshold. As the spatial diversity techniques in the form of multiple-input-multipleoutput (MIMO) systems have the potential to enhance capacity significantly, the above work has been extended to peer-to-peer MIMO relay networks. Transceiver and relay beamforming design based on minimum mean-square error (MSE) criterion has been proposed. Establishing uplink downlink MSE duality, an alternating algorithm has been developed. A scenario where multiple users are served by both the BS and a MIMO relay is considered and a joint beamforming technique for the BS and the MIMO relay is proposed. With the motivation of optimising the transmission power at both the BS and the relay, an interference precoding design is presented that takes into account the knowledge of the interference caused by the relay to the users served by the BS. Recognizing joint beamformer design for multiple BSs has the ability to reduce interference in the network significantly, cooperative multi-cell beamforming design is proposed. The aim is to design multi-cell beamformers to maximize the minimum SINR of users subject to individual BS power constraints. In contrast to all works available in the literature that aimed at balancing SINR of all users in all cells to the same level, the SINRs of users in each cell is balanced and maximized at different values. This new technique takes advantage of the fact that BSs may have different available transmission powers and/or channel conditions for their users

    Feasibility and performance of relay-aided interference alignment

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    In current wireless radio communications systems, the multiuser interference is a major performance-limiting factor due to the scarceness of spectrum. Recently, it has been discovered that every user is able to get “half the cake” using a novel interference management approach known as IA. IA is able to achieve the DoFs of many multiuser interference networks, leading to outstanding performances in the high-SNR regime. This thesis focuses on the topic of relay-aided IA.In gegenwärtigen Funkkommunikationssystemen ist jedoch aufgrund der Begrenztheit des Spektrums die Mehrnutzer-Interferenz ein vornehmlicher performanzbegrenzender Faktor. Vor kurzem wurde entdeckt, dass jeder Benutzer mit einem neuartigen, als Interference Alignment bezeichneten, Interferenzreduktionsverfahren „den halben Kuchen“ gewissermaßen bekommen kann. IA ist in der Lage, die DoFs von vielen Mehrnutzer-Interferenznetzwerken zu erreichen, was zu herausragenden Leistungen im Bereich hoher SNRs führt. Die vorliegende Arbeit konzentriert sich auf dem Gebiet des relaisunterstützten IA

    Resource allocation and optimization techniques in wireless relay networks

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    Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks

    Efficient Scheduling Algorithms for Wireless Resource Allocation and Virtualization in Wireless Networks

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    The continuing growth in demand for better mobile broadband experiences has motivated rapid development of radio-access technologies to support high data rates and improve quality of service (QoS) and quality of experience (QoE) for mobile users. However, the modern radio-access technologies pose new challenges to mobile network operators (MNO) and wireless device designers such as reducing the total cost of ownership while supporting high data throughput per user, and extending battery life-per-charge of the mobile devices. In this thesis, a variety of optimization techniques aimed at providing innovative solutions for such challenges are explored. The thesis is divided into two parts. In the first part, the challenge of extending battery life-per-charge is addressed. Optimal and suboptimal power-efficient schedulers that minimize the total transmit power and meet the QoS requirements of the users are presented. The second outlines the benefits and challenges of deploying wireless resource virtualization (WRV) concept as a promising solution for satisfying the growing demand for mobile data and reducing capital and operational costs. First, a WRV framework is proposed for single cell zone that is able to centralize and share the spectrum resources between multiple MNOs. Consequently, several WRV frameworks are proposed, which virtualize the spectrum resource of the entire network for cloud radio access network (C-RAN)- one of the front runners for the next generation network architecture. The main contributions of this thesis are in designing optimal and suboptimal solutions for the aforementioned challenges. In most cases, the optimal solutions suffer from high complexity, and therefore low-complexity suboptimal solutions are provided for practical systems. The optimal solutions are used as benchmarks for evaluating the suboptimal solutions. The results prove that the proposed solutions effectively contribute in addressing the challenges caused by the demand for high data rates and power transmission in mobile networks
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