Electrical and Electronic Engineering - Theses

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    Resource optimization for future wireless communications and energy harvesting systems with coordinated transmission
    Luo, Bing ( 2019)
    Dense-cell deployment with coordinated multiple point transmission has been widely investigated to minimize inter-cell interference. Depending on the knowledge of channel state information and whether joint coding and signal processing are performed at the cooperative transmitters, coordinated transmission can be divided into coherent and non-coherent transmission. In the first half of the thesis, we study optimal power allocation for capacity maximization with coherent and non-coherent transmission, in which K coordinated transmitters coherently/non-coherently allocate power across N subchannels under joint total and individual power constraints. This allows the system to limit the overall energy consumption for cost and/or green factors, while also preventing individual transmitters to overdrive their high-powered amplifiers. For coherent coordinated transmission, we derive a new optimal co-phasing power allocation which shows that the optimal power allocation must follow a particular proportional rule. This result highlights that the optimal power allocation for transmitters with individual power constraints is different from waterfilling, as more power is not necessarily allocated to the subchannels with better channel conditions. In the non-coherent coordinated transmission case, we show that the optimal power allocation solution has an interesting sparse feature that among N subchannels, at most K-1 subchannels can be allocated power for joint transmission by multiple transmitters, and the rest of the subchannels must be served by a single transmitter. As wireless devices (e.g., Internet of things device and wireless sensor) become more pervasive, there is an ever-increasing interest for powering electronic devices wirelessly. In order to avoid the high radiation intensity and expand coverage, distributed but coordinated wireless power transfer (WPT) using energy beamforming is considered as a promising technology to address the energy scarcity problem. In the second half of the thesis, we study an optimal distributed energy beamforming strategy for total harvested power maximization, where K coordinated energy transmitters (CETs) coherently transmit energy over N subchannels. Under joint total and individual antenna power constraints, we derive the optimal power allocation rule which reveals that all K CETs will participate in energy beamforming with T < K CETs transmitting with their maximum individual powers due to the total power constraint. Nevertheless, the optimal WPT strategy is that no more than T+1 subchannels are selected for power allocation regardless of the channel conditions. Finally, we analyse a distributed multi-antenna WPT system, where each CET k is equipped with M antennas and has a transmit power constraint Pk. We show that the optimal power allocation has similar properties as coherent wireless information transmission. However, the optimal WPT strategy is that no more than K subchannels are selected for power allocation regardless of the channel conditions or the number of antennas in each CET.
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    Optimal and Game-theoretic Resource Allocations for Multiuser Wireless Energy-Harvesting and Communications Systems
    George, Jithin ( 2019)
    The fifth generation (5G) of wireless cellular networks will see a paradigm shift towards extreme base station densification with massive amounts of data transmissions, massive number of mobile users, and massive number of antenna systems. To support this, network resources such as power and bandwidth will need to be efficiently allocated to multiple nodes with consideration for energy-efficiency, fairness, security, and scalability. The advancements in wireless power transfer have enabled high power conversion efficiency over practical transmission ranges. This can result in overcoming the energy constraints of wireless nodes such as mobile users, sensors, and IoT, and cutting the wires to recharging stations. As such, this results in a new dimension to resource allocation for traditional information-based communication systems due to extra consideration of energy harvested. The focus of this thesis is to design new resource allocation frameworks based on optimization-techniques and game-theory for future wireless energy-harvesting and communications systems. We consider the two main wireless power transfer (WPT) and communications technologies namely 1) Simultaneous wireless information and power transfer (SWIPT) which transfer power and information from the same access point, and 2) wireless-powered communications (WPC) with separate energy access points (EAPs) for power signals and data access points (DAPs) for information signals. For multi-user SWIPT systems with fairness constraints, we developed a max-min energy harvesting solution while satisfying the sum power budget and minimum user rate. By using the max-min energy harvesting solution we solved the dual problem which is the max-min rate satisfying minimum user energy-harvesting levels and sum power constraints. All these problems are NP-hard in nature, thus, we decompose the problem into distinct stages and developed efficient algorithms to tackle them. Furthermore, we provided insights on the total transmit power, channel bandwidth and minimum required rate considerations for the practical implementation and feasibility of energy harvesting in SWIPT systems. Security is a key concern in SWIPT systems due to the broadcast transmission of energy and information signals. Towards this end, we have developed a new optimization algorithm for secure SWIPT in OFDMA networks with multiple legitimate users communicating in the presence of an eavesdropper. The objective of our optimization framework is to maximize the total harvested-power satisfying a minimum secrecy capacity constraint for each legitimate user. We also optimized the power splitting ratio between the information and power transmission for legitimate users. To obtain deeper insights, we investigated novel game-theoretic formulations to facilitate individual user utility maximization when the users are rational players. We designed a Stackelberg game with users as multiple leaders deciding power splitting ratios as their strategy, and the base station as the follower deciding transmit power. For WPC, we proposed a new model where the EAP also acts as a relay for information signals between the users and the DAP. Specifically, we design an energy trading game between multiple relay-energy access points (REAP) and DAPs for buying energy for users. The same REAPs can be used for relaying information to the DAP based on the channel states. We exploited the cooperative communication advantages for information transfer in energy harvesting. Numerical examples for showing the effectiveness of all the proposed algorithms are given.
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    Resource allocation in energy harvesting relay networks
    Pilanawithana, Bhathiya Maneendra ( 2019)
    As the demand for low power Internet-of-things (IoT) devices rises, connectivity becomes a major challenge. Cooperative communication with radio frequency energy harvesting can improve connectivity. Sensor nodes which do not have a direct link to a computation node may form a communication link through other nodes that act as relays. In an energy-scarce environment, low power devices tend to go into a sleep state whenever they do not generate information to transmit. This is counterproductive to cooperative communication which requires nodes to transmit information from other nodes. A promising alternative is to use radio frequency energy harvesting at the relay node. In this thesis we consider a three-node communication network in which a source node communicates with a destination node through a relay node. The direct link between source to destination does not exist, and the relay node relies on the energy harvested from the source transmitted information signal. Our goal is to determine the source transmit power, relay transmit power and relay energy harvesting parameters such that the performance of the system is optimized. Moreover, a long-term battery at the relay can reduce the randomness in relay transmit power. This can be exploited by an efficient resource allocation policy to improve the system performance. However, energy in the battery depends on the resource allocations decisions made earlier, which makes the analysis of the system more complicated than the situation where no long-term battery is available at the relay. We determine the optimal resource allocation for both situations, which can be used to compare the performance gain due to relay battery.
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    Resource allocation in OFDM cellular networks
    Thanabalasingham, Thayaparan ( 2006-12)
    The efficient use of radio resources is crucial in order for future wireless systems to be able to meet the demand for high speed data communication services. Orthogonal Frequency Division Multiplexing (OFDM) is an important technology for future wireless systems as it offers numerous advantages over other existing technologies, such as robust performance over multipath fading channels and the ability to achieve high spectral efficiency. Dynamic resource allocation can fully exploit the advantages of OFDM, especially in multiple user systems. In this thesis, we investigate a resource allocation problem in a multiple user, multiple cell OFDM cellular network focusing on downlink communications. (For complete abstract open document)
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    Resource allocation in cognitive radio networks
    LIMMANEE, ATHIPAT ( 2012)
    This thesis focuses on optimal power allocation problems for various types of spectrum-sharing based cognitive radio networks in the presence of delay-sensitive primary links. To guarantee the quality of service in the delay-sensitive primary network, primary user’s outage probability constraint (POC) is imposed such that the transmission outage probability of each primary user is confined under the predefined threshold. We first consider a cognitive radio network consisting of a secondary user (SU) equipped with orthogonal frequency-division multiplexing (OFDM) technology able to access N randomly fading frequency bands for transmitting delay-insensitive as well as delay-sensitive traffic. Each band is licensed to an individual single-antenna and delay-sensitive primary user (PU) whose quality of service is assured by a POC. Assuming full channel state information (CSI) is available at the secondary network, we solve the SU’s ergodic capacity maximization problem subject to SU’s average transmit power, SU’s outage probability constraints (SOC) and all POCs by using a rigorous probabilistic power allocation technique. A suboptimal power control policy is also proposed to reduce the high computational complexity when N is large. Next, we study cognitive broadcast channels with a single-antenna secondary base station (SBS) and M single-antenna secondary receivers (SRs) sharing the same spectrum band with one single-antenna and delay-sensitive PU. The SBS aims to maximize the ergodic sum downlink throughput to all M SRs subject to a POC and a transmit power constraint at the SBS. With full CSI available at the secondary network, the optimal solution reveals that at each timeslot SBS will choose the SR with the highest direct channel power gain and allocate the timeslot to that user. The opportunistic scheduling aspect from the optimality condition allows us to further analyze the downlink throughput scaling behavior in Rayleigh fading channel as M grows large. We then examine a cognitive multiple-access channels with a single-antenna SBS and M single-antenna secondary transmitters sharing the same spectrum band with a single-antenna and delay-sensitive PU. Under an average transmit power constraint in each secondary transmitters and a POC at the primary link, we characterize the ergodic capacity region and two outage capacity regions, i.e. common outage capacity region and individual outage capacity region, in the secondary uplink network by exploiting the polymatroid structure of the problems. Also, the derivation of the associated optimal power allocation schemes are provided. The optimal solutions for the problems demonstrate that successive decoding is optimal and the decoding order can be solved explicitly as a function of joint channel state. Finally, we investigate a transmit power allocation problem for minimizing outage probability of a single-antenna SU subject to a POC at a delay-sensitive and single-antenna PU and an average transmit power constraint at the SU, providing that the SU has quantized channel side information via B-bit feedback from the band manager. By using nearest neighbourhood condition, we can derive the optimal channel partition structure for the vector channel space, making Karush-Kuhn-Tucker condition applicable as a necessary condition for finding a locally optimal solution. We also propose another low-complexity suboptimal algorithm. Numerical results show that the SU’s outage probability performance from the suboptimal algorithm approaches the SU’s outage probability performance in the locally-optimal algorithm as the number of feedback bits, B, increases. Besides, we include the asymptotic analysis on the SU’s outage probability when B is large.
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    Topics in resource allocation in wireless sensor networks
    Li, Chaofeng (James) ( 2008)
    The focus of this thesis is on the resource allocation problems in wireless sensor and cooperative networks. Typically, wireless sensor networks operate with limited energy and bandwidth are often required to meet some specified Quality-of-Service (QoS) constraints. The ultimate objective for the majority of the problems considered in this thesis is to save battery energy and maximize the network lifetime. In the first part of this thesis, we employ complex mathematical models to emulate a variety of power drains in wireless sensor nodes. In the first instance, we address a lifetime optimization problem of a wireless TDMA/CDMA sensor network for joint transmit power and rate allocations. The effect of fast fading is captured by including rate outage and link outage constraints on each link. After that, a single-hop wireless sensor network is deployed for a certain application - to estimate a Gaussian source within a pre-specified distortion threshold. In this part, we consider lifetime maximization, in different multiple access protocols such as TDMA, an interference limited non-orthogonal multiple access (NOMA) and an idealized Gaussian multiple access channel. This problem is further studied in a multi-hop scenario where sensing and receiving powers are also included in addition to transmission power. Finally, we investigate a balancing problem between the source coding and transmission power for video wireless sensor systems where the sensor node is required to send the collected video clips, through wireless media, to a base station within a corresponding distortion threshold. All these energy saving and lifetime optimization problems in sensor networks can be formulated via nonlinear nonconvex optimization problems, which are generally hard to solve. However, with favourable variable substitution and reasonable approximation, most of these problems are shown to be convex. The only exception is the Gaussian source esitmation problem in NOMA scenario for which we provide a simple successive convex approximation based algorithm for the NOMA case that converges fast to a suboptimal solution. In the second part of the thesis, we propose an optimal power allocation scheme with a K-block coding delay constraint on data transmission using a three node cooperative relay network assuming a block fading channel model. Channel information is fed back to the transmitter only in a causal fashion, so that the optimal power allocation strategy is only based on the current and past channel gains. We consider the two simplest schemes for information transmission using a three node (a source, a relay and a destination) relay network, namely the amplify and forward (AF) and decode and forward (DF) protocols. We use the dynamic programming methodology to solve the (K-block delay constrained) expected capacity maximization problem and the outage probability minimization problem with a short term sum power (total transmission power of the source and the relay) constraint. The main contribution of the thesis is a comprehensive suite of power minimization and lifetime maximization methods that can be used in wireless sensor networks. We present several such applications and extensive numerical examples at the end of each chapter.