Wireless Information and Power Transfer in Communication Networks: Performance Analysis and Optimal Resource Allocation

Energy harvesting is considered as a prominent solution to supply the energy demand for low-power consuming devices and sensor nodes. This approach relinquishes the requirements of wired connections and regular battery replacements. This thesis analyzes the performance of energy harvesting communication networks under various operation protocols and multiple access schemes. Furthermore, since the radio frequency signal has energy, in addition to conveying information, it is also possible to power energy harvesting component while establishing data connectivity with information-decoding component. This leads to the concept of simultaneous wireless information and power transfer. The central goal of this thesis is to conduct a performance analysis in terms of throughput and energy efficiency, and determine optimal resource allocation strategies for wireless information and power transfer. In the first part of the thesis, simultaneous transfer of information and power through wireless links to energy harvesting and information decoding components is studied considering finite alphabet inputs. The concept of non-uniform probability distribution is introduced for an arbitrary input, and mathematical formulations that relate probability distribution to the required harvested energy level are provided. In addition, impact of statistical quality of service (QoS) constraints on the overall performance is studied, and power control algorithms are provided. Next, power allocation strategies that maximize the system energy efficiency subject to peak power constraints are determined for fading multiple access channels. The impact of channel characteristics, circuit power consumption and peak power level on the node selection, i.e., activation of user equipment, and the corresponding optimal transmit power level are addressed. Initially, wireless information transfer only is considered and subsequently wireless power transfer is taken into account. Assuming energy harvesting components, two scenarios are addressed based on the receiver architecture, i.e, having separated antenna or common antenna for the information decoding and energy harvesting components. In both cases, optimal SWIPT power control policies are identified, and impact of the required harvested energy is analyzed. The second line of research in this thesis focuses on wireless-powered communication devices that operate based on harvest-then-transmit protocol. Optimal time allocation for the downlink and uplink operation interval are identified formulating throughput maximization and energy-efficiency maximization problems. In addition, the performance gain among various types of downlink-uplink operation protocols is analyzed taking into account statistical QoS constraints. Furthermore, the performance analysis of energy harvesting user equipment is extended to full-duplex wireless information and power transfer as well as cellular networks. In full-duplex operation, optimal power control policies are identified, and the significance of introducing non-zero mean component on the information-bearing signal is analyzed. Meanwhile, SINR coverage probabilities, average throughput and energy efficiency are explicitly characterized for wireless-powered cellular networks, and the impact of downlink SWIPT and uplink mmWave schemes are addressed. In the final part of the thesis, energy efficiency is considered as the performance metric, and time allocation strategies that maximize energy efficiency for wireless powered communication networks with non-orthogonal multiple access scheme are determined. Low complex algorithms are proposed based on Dinkelbach’s method. In addition, the impact of statistical QoS constraints imposed as limitations on the buffer violation probabilities is addressed

Wireless industrial monitoring and control networks: the journey so far and the road ahead

While traditional wired communication technologies have played a crucial role in industrial monitoring and control networks over the past few decades, they are increasingly proving to be inadequate to meet the highly dynamic and stringent demands of today’s industrial applications, primarily due to the very rigid nature of wired infrastructures. Wireless technology, however, through its increased pervasiveness, has the potential to revolutionize the industry, not only by mitigating the problems faced by wired solutions, but also by introducing a completely new class of applications. While present day wireless technologies made some preliminary inroads in the monitoring domain, they still have severe limitations especially when real-time, reliable distributed control operations are concerned. This article provides the reader with an overview of existing wireless technologies commonly used in the monitoring and control industry. It highlights the pros and cons of each technology and assesses the degree to which each technology is able to meet the stringent demands of industrial monitoring and control networks. Additionally, it summarizes mechanisms proposed by academia, especially serving critical applications by addressing the real-time and reliability requirements of industrial process automation. The article also describes certain key research problems from the physical layer communication for sensor networks and the wireless networking perspective that have yet to be addressed to allow the successful use of wireless technologies in industrial monitoring and control networks

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

Resource management in QoS-aware wireless cellular networks

2011 Summer.Includes bibliographical references.Emerging broadband wireless networks that support high speed packet data with heterogeneous quality of service (QoS) requirements demand more flexible and efficient use of the scarce spectral resource. Opportunistic scheduling exploits the time-varying, location-dependent channel conditions to achieve multiuser diversity. In this work, we study two types of resource allocation problems in QoS-aware wireless cellular networks. First, we develop a rigorous framework to study opportunistic scheduling in multiuser OFDM systems. We derive optimal opportunistic scheduling policies under three common QoS/fairness constraints for multiuser OFDM systems--temporal fairness, utilitarian fairness, and minimum-performance guarantees. To implement these optimal policies efficiently, we provide a modified Hungarian algorithm and a simple suboptimal algorithm. We then propose a generalized opportunistic scheduling framework that incorporates multiple mixed QoS/fairness constraints, including providing both lower and upper bound constraints. Next, taking input queues and channel memory into consideration, we reformulate the transmission scheduling problem as a new class of Markov decision processes (MDPs) with fairness constraints. We investigate the throughput maximization and the delay minimization problems in this context. We study two categories of fairness constraints, namely temporal fairness and utilitarian fairness. We consider two criteria: infinite horizon expected total discounted reward and expected average reward. We derive and prove explicit dynamic programming equations for the above constrained MDPs, and characterize optimal scheduling policies based on those equations. An attractive feature of our proposed schemes is that they can easily be extended to fit different objective functions and other fairness measures. Although we only focus on uplink scheduling, the scheme is equally applicable to the downlink case. Furthermore, we develop an efficient approximation method--temporal fair rollout--to reduce the computational cost