UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
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Item Energy Harvesting Communication Networks: Online Policies, Temperature Considerations, and Age of Information(2018) Baknina, Abdulrahman Mohamed Hanafy Mahmoud; Ulukus, Sennur; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation focuses on characterizing energy management policies for energy harvesting communication networks in the presence of stochastic energy arrivals and temperature constraints. When the energy arrivals are stochastic and are known only causally at the transmitter, we study two performance metrics: throughput and age of information (AoI). When the energy harvesting system performance is affected by the change of the temperature, we consider the throughput metric. When the energy arrivals are stochastic, we study the throughput maximization problem for several network settings. We first consider an energy harvesting broadcast channel where a transmitter serves data to two receivers on the downlink. The battery at the transmitter in which the harvested energy is stored is of finite size. We focus on online transmission schemes where the transmitter knows the energy arrivals only causally as they happen. We consider the case of general independent and identically distributed (i.i.d.) energy arrivals, and propose a near-optimal strategy coined fractional power constant cut-off (FPCC) policy. We show that the FPCC policy is near-optimal in that it yields rates that are within a constant gap from the optimal rate region, for all system parameters. Next, we study online transmission policies for a two-user multiple access channel where both users harvest energy from nature. The energy harvests are i.i.d. over time, but can be arbitrarily correlated between the two users. The transmitters are equipped with arbitrary but finite-sized batteries. We propose a distributed fractional power (DFP) policy, which users implement distributedly with no knowledge of the other user's energy arrival or battery state. We show that the proposed DFP is near-optimal as in the broadcast channel case. Then, we consider online power scheduling for energy harvesting channels in which the users incur processing cost per unit time that they are on. The presence of processing costs forces the users to operate in a bursty mode. We consider the single-user and two-way channels. For the single-user case, we consider the case of the general i.i.d.~energy arrivals. We propose a near-optimal online policy for this case. We then extend our analysis to the case of two-way energy harvesting channels with processing costs; in this case, the users incur processing costs for being on for transmitting or receiving data. Our proposed policy is distributed, which users can apply independently with no need for cooperation or coordination between them. Next, we consider a single-user channel in which the transmitter is equipped with finite-sized data and energy buffers. The transmitter receives energy and data packets randomly and intermittently over time and stores them in the finite-sized buffers. The arrival amounts are known only causally as they happen. We focus on the special case when the energy and data arrivals are fully-correlated. We propose a structured policy and bound its performance by a multiplicative gap from the optimal. We then show that this policy \emph{is optimal} when the energy arrivals dominate the data arrivals, and is \emph{near-optimal} when the data arrivals dominate the energy arrivals. Then, we consider another performance metric which captures the freshness of data, i.e., AoI. For this metric, we first consider an energy harvesting transmitter sending status updates to a receiver over an erasure channel. The energy arrivals and the channel erasures are i.i.d. and Bernoulli distributed in each slot. In order to combat the effects of the erasures in the channel and the uncertainty in the energy arrivals, we use channel coding to encode the status update symbols. We consider two types of channel coding: maximum distance separable (MDS) codes and rateless erasure codes. For each of these models, we study two achievable schemes: best-effort and save-and-transmit. We analyze the average AoI under each of these policies. We show that rateless coding with save-and-transmit outperforms all other schemes. Next, we consider a scenario where the transmitter harvests i.i.d. Bernoulli energy arrivals and status updates carry information about an independent message. The transmitter encodes this message into the timings of the status updates. The receiver needs to extract this encoded information, as well as update the status of the observed phenomenon. The timings of the status updates, therefore, determine both the AoI and the message rate (rate). We study the trade-off between the achievable message rate and the achievable average AoI. We propose several achievable schemes and compare their rate-AoI performances. Then, with the motivation to understand the effects of temperature sensitivity on wireless data transmission performance for energy harvesting communication networks, we study several temperature models. We assume non-causal knowledge of the energy arrivals. First, we consider throughput maximization in a single-user energy harvesting communication system under continuous time energy and temperature constraints. We model three main temperature related physical defects in wireless sensors mathematically, and investigate their impact on throughput maximization. Specifically, we consider temperature dependent energy leakage, effects of processing circuit power on temperature, and temperature increases due to the energy harvesting process itself. In each case, we determine the optimum power schedule. Next, different from the previous work, we consider a discrete time system where transmission power is kept constant in each slot. We consider two models that capture different effects of temperature. In the first model, the temperature is constrained to be below a critical temperature at all time instants; we coin this model as explicit temperature constrained model. We investigate throughput optimal power allocation for multiple energy arrivals under general, as well as temperature and energy limited regimes. In the second model, we consider the effect of the temperature on the channel quality via its influence on additive noise power; we coin this model as implicit temperature constrained model. In this model, the change in the variance of the additive noise due to previous transmissions is non-negligible. In particular, transmitted signals contribute as interference for all subsequent slots and thus affect the signal to interference plus noise ratio (SINR). In this case, we investigate throughput optimal power allocation under general, as well as low and high SINR regimes. Finally, we consider the case in which implicit and explicit temperature constraints are simultaneously active. Finally, we extend the discrete time explicit temperature constraint model to a multi-user setting. We consider a two-user energy harvesting multiple access channel where the temperatures of the nodes are affected by the electromagnetic waves due to data transmission. We study the optimal power allocations when the temperatures of the nodes are subject to peak temperature constraints, where each node has a different peak temperature requirement and the nodes have different temperature parameters. We study the optimal power allocation in this case and derive sufficient conditions under which the rate region collapses to a single pentagon.Item EQUILIBRIUM ANALYSIS AND CONTROL FOR DESIGN OF PACKET RESERVATION MULTIPLE ACCESS PROTOCOLS(2010) Sharifi, Amirali; Abed, Eyad H; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The Packet Reservation Multiple Access (PRMA) protocol and its variants have been considered as possible access schemes for communication media for indoor communications, terrestrial communications and satellite communications. Most recently, PRMA (and its variants) has been considered for applications such as beyond third generation and/or fourth generation communication systems, cooperative communication, and multimedia communication in dynamic environments. In this dissertation, equilibrium behavior of general voice and/or data systems employing PRMA are studied along with means for control of this behavior. The main objective is to determine conditions guaranteeing a unique equilibrium for these systems, as multistability can result in an unacceptable user experience. Systems considered include voice systems, voice and data systems, and voice systems with high propagation delay (these are studied both for an error-free channel and a random error channel). Also, various control schemes are introduced and their effect on these system is analyzed at equilibrium. Control schemes considered include a price based control, state estimation-based control, and control using multiple transmission power and capture. For each type of control, the effect of the control on the equilibrium structure of the system is studied, in the spirit of the methodology of bifurcation control. In bifurcation control, the number and nature of steady state solutions of a system are managed by appropriate design of system control laws. Several sufficient conditions for uniqueness of operating points of the PRMA systems under the studied control schemes is determined. Numerical analysis of the equilibrium equations of the systems is provided to support the analytical studies. The equilibrium behavior of voice systems and voice-data systems employing frame-based PRMA is also studied. Effects of price based control on these systems is analyzed. Further, the price based control studied in conjunction with the PRMA systems is extended to a finite buffer finite user slotted ALOHA system, and the equilibrium behavior of the system is studied using a tagged user approach. Among the contributions of the dissertation are analytical sufficient conditions guaranteeing a unique equilibrium point for the various classes of systems studied, control law designs that result in improved system capacity, and extensive numerical studies including comparisons with two previously proposed approaches. Analysis is also given proving the Markovian nature of the system's stochastic dynamics (under some basic assumptions) and the existence of a unique stationary probability law.Item Multipath Routing Algorithms for Communication Networks: Ant Routing and Optimization Based Approaches(2009) Purkayastha, Punyaslok; Baras, John S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this dissertation, we study two algorithms that accomplish multipath routing in communication networks. The first algorithm that we consider belongs to the class of Ant-Based Routing Algorithms (ARA) that have been inspired by experimental observations of ant colonies. It was found that ant colonies are able to `discover' the shorter of two paths to a food source by laying and following `pheromone' trails. ARA algorithms proposed for communication networks employ probe packets called ant packets (analogues of ants) to collect measurements of various quantities (related to routing performance) like path delays. Using these measurements, analogues of pheromone trails are created, which then influence the routing tables. We study an ARA algorithm, proposed earlier by Bean and Costa, consisting of a delay estimation scheme and a routing probability update scheme, that updates routing probabilities based on the delay estimates. We first consider a simple scenario where data traffic entering a source node has to be routed to a destination node, with N available parallel paths between them. An ant stream also arrives at the source and samples path delays en route to the destination. We consider a stochastic model for the arrival processes and packet lengths of the streams, and a queuing model for the link delays. Using stochastic approximation methods, we show that the evolution of the link delay estimates can be closely tracked by a deterministic ODE (Ordinary Differential Equation) system. A study of the equilibrium points of the ODE enables us to obtain the equilibrium routing probabilities and the path delays. We then consider a network case, where multiple input traffic streams arriving at various sources have to be routed to a single destination. For both the N parallel paths network as well as for the general network, the vector of equilibrium routing probabilities satisfies a fixed point equation. We present various supporting simulation results. The second routing algorithm that we consider is based on an optimization approach to the routing problem. We consider a problem where multiple traffic streams entering at various source nodes have to be routed to their destinations via a network of links. We cast the problem in a multicommodity network flow optimization framework. Our cost function, which is a function of the individual link delays, is a measure of congestion in the network. Our approach is to consider the dual optimization problem, and using dual decomposition techniques we provide primal-dual algorithms that converge to the optimal routing solution. A classical interpretation of the Lagrange multipliers (drawing an analogy with electrical networks) is as `potential differences' across the links. The link potential difference can be then thought of as `driving the flow through the link'. Using the relationships between the link potential differences and the flows, we show that our algorithm converges to a loop-free routing solution. We then incorporate in our framework a rate control problem and address a joint rate control and routing problem.