Enerji hasadı yapan kablosuz ağlarda kullanıcı işbirliği ve kaynak tahsisi

Yeni nesil haberleşme sistemlerinde, pillere ya da şehir elektriğine bağımlı olarak çalışan klasik haberleşme bileşenlerinin yerlerini, enerjilerini çevreden hasat eden, çevreye duyarlı ve uzun kullanım ömrüne sahip bileşenlere bırakacağı öngörülmektedir. Bu nedenle, bilinen haberleşme protokollerinin, enerjinin aralıklı olarak geldiği, ve gönderilerin anlık enerji kısıtlarına tabi olduğu durumlara uygun olarak baştan ele alınması, ve enerji hasadı koşulları altında kuramsal performans üst limitlerinin baştan belirlenmesi gerekmektedir. Bu projede, tüm enerjilerini doğadan hasat eden işbirlikli haberleşme ağlarında, kaynakları etkin kullanarak ağ performansını artıran ve ömrünü uzatan gönderim protokolleri tasarlanmıştır. Böylece, işbirlikli kablosuz ağlarda basit çoklu erişim ya da aktarım kanal modellerinin ötesine geçilmiş; farklı kullanıcılarda anlık olarak farklı miktarlarda biriktirilen enerjinin beraberinde getirdiği enerji çeşitleme kazancı ile işbirliği kazancından bir arada faydalanılması sağlanmıştır. Düğümlerin kendi enerjilerini iletim sırasında çevrelerinden temin ettikleri, ve biribirleri ile gerek veri, gerekse enerji aktarımı ile yardımlaşabildikleri durumlar için, • Bilgi kuramsal bir yaklaşım kullanılarak, gerek gecikme kısıtlı, gerekse gecikmeye toleranslı durumlar için, blok Markov kodlama ve geriye doğru kodçözme tabanlı yeni işbirlikli kodlama teknikleri geliştirilmiş, ve karşılık gelen erişilebilir veri hızları elde edilmiş, • Toplam veri hızı veya veri gönderim bölgelerini enbüyükleyen kaynak tahsisi algoritmaları geliştirilmiş, • Hasat edilen enerji ve kanal durumlarının gönderim, aktarım, ya da enerjinin depolanması kararlarını nasıl etkilediği incelenmiş, temel bazı ödünleşimler belirlenmiş, • Verinin ve hasat edilen enerjinin gönderi devam ederken aralıklı geldiği durumda en iyi veri hızı ve güç çizelgelemesi bulunmuş, • İşbirlikli haberleşme için kritik olan, hem alıcı hem de verici olarak davranan düğümlerdeki kodçözme maliyeti kısıtları dikkate alınarak işbirliğinden net kazancı eniyileyen politikalar geliştirilmiş, • Düğümlerin biribirlerine enerji de gönderebildikleri durumda, işbirlikli veri iletişimi ile enerji transferi yoluyla işbirliği senaryoları birlikte incelenip, en iyi kaynak tahsisi stratejisi belirlenmiş, • Hasat edilen kaydedildiği bataryaların sınırlı kapasitesi olması durumunda gelen enerjinin ziyan edilmemesini garanti eden en iyi kaynak yönetimi algoritmaları önerilmiştir. Elde edilen sonuçlar, gerek veri, gerekse enerji işbirliğinin, enerji hasat eden sistemlerde, özellikle enerji çeşitlemesinden kazanç sağlamak için çok faydalı yaklaşımlar olduğuna işaret etmektedir.In new generation wireless systems, traditional communication components which rely on batteries or the electrical grid are expected to ve replaced by more environment-conscious, energy harvesting components with longer lifetime. Therefore, known communication protocols need to be reconsidered from scratch to adapt to situations where the transmissions are subject to instantaneous energy constraints caused by intermittent energy arrivals, and their theoretical performance upper bounds need to be re-derived under energy harvesting constraints. In this project, we design transmission protocols that maximize the network performance and lifetime by efficiently allocating resources, for communication networks that rely only on energy harvested from their surroundings. We go beyond simple multiple access or relay models, and jointly take advantage of the energy diversity provided by the variable nature of the energy arrivals at different users, and cooperative diversity. For scenarios where the nodes harvest their own enery during transmission, and are able to cooperate both at data and battery level, • we approach the system from an information theoretic perspective and develop new encoding and decoding techniques, based on block Markov coding and backward decoding, that can be used in delay constrained and delay tolerant communication; and characterize their achievable rates, • we develop resource allocation algorithms that maximize the total rate or departure region, • we investigate the effect of energy arrival profiles and channel qualities on transmission, bi-directional relaying and energy saving decisions, and determine some fundamental tradeoffs, • we find the optimal power and rate scheduling policy when data, as well as energy arrives intermittently during transmission, • we obtain the optimal policies that maximize the net gain from cooperation, taking into account the decoding costs at the transceiver nodes, • we develop jointly optimal energy and data cooperation strategies, when energy can be exchanged wirelessly • we propose scheduling optimization algorithms that guarantee that energy is not wasted, taking into account practical battery limitations at the energy harvesting nodes. The results obtained point to the conclusion that data and energy cooperation are significantly useful approaches that take advantage of the inherent energy diversity provided by the energy harvesting communication systems.TÜBİTA

Energy harvesting cooperative multiple access channel with decoding costs

We consider an energy harvesting cooperative multiple access channel (AC) with decoding costs. In this setting, users cooperate at the physical layer (data cooperation) in order to increase the achievable rates. Data cooperation comes at the expense of decoding costs: each user spends some amount of its harvested energy to decode the message of the other user, before forwarding both messages to the receiver. The decoding power spent is an increasing convex function of the incoming message rate. We characterize the optimal power scheduling policies that achieve the boundary of the maximum departure region subject to energy causality constraints and decoding costs by using a generalized water-filling algorithm.This work was supported by TUBITAK Grant 113E556, and NSF Grants CNS 13-14733, CCF 14-22111, CCF 14-22129 and CNS 15-26608Publisher's Versio

Energy Harvesting Communication Networks with System Costs

This dissertation focuses on characterizing optimal energy management policies for energy harvesting communication networks with system costs. The system costs that we consider are the cost of circuitry to be on (processing cost) at the transmitters, cost of decoding at the receivers, cost of moving to harvest more energy in mobile energy harvesting nodes, and the cost of collecting measurements (sampling cost) from physical phenomena. We first consider receiver decoding costs in networks where receivers, in addition to transmitters, rely on energy harvested from nature to communicate. Energy harvested at the receivers is used to decode their intended messages, and is modeled as a convex increasing function of the incoming rate. With the goal of maximizing throughput by a given deadline, we study single-user and multi-user settings, and show that decoding costs at the receivers can be represented as generalized data arrivals at the transmitters. This introduces a further coupling between the transmitters and receivers of the network and allows us to characterize optimal policies by moving all constraints to the transmitter side. Next, we study the decoding cost effect on energy harvesting cooperative multiple access channels, where users employ data cooperation to increase their achievable rates. Data cooperation requires each user to decode the other user's data before forwarding it to the destination, which uses up some of the harvested energy. With the presence of decoding costs, we show that data cooperation may not be always helpful; if the decoding costs are relatively high, then sending directly to the receiver without data cooperation between the users achieves higher throughput. When cooperation is helpful, we determine the optimum allocation of available energy between decoding cooperative partner's data and forwarding it to the destination. We then study the impact of adding processing costs, on top of decoding costs, in energy harvesting two-way channels. Processing costs are the amounts of energy spent for circuitry operation, and are incurred whenever a user is communicating. We show that due to processing costs, transmission may become bursty, where users communicate through only a portion of the time. We develop an optimal scheme that maximizes the sum throughput by a given deadline under both decoding and processing costs. Next, we focus on online policies. We consider a single-user energy harvesting channel where the transmitter is equipped with a finite-sized battery, and the goal is to maximize the long term average utility, for general concave increasing utility functions. We show that fixed fraction policies are near optimal; they achieve a long term average utility that lies within constant multiplicative and additive gaps from the optimal solution for all battery sizes and all independent and identically distributed energy arrival patterns. We then consider a specific scenario of a utility function that measures the distortion of Gaussian samples communicated over a Gaussian channel. We formulate two problems: one with, and the other without sampling costs, and design near optimal fixed fraction policies for the two problems. Then, we consider another aspect of costs in energy harvesting single-user channels, that is, the energy spent in physical movement in search of better energy harvesting locations. Since movement has a cost, there exists a tradeoff between staying at the same location and moving to a new one. Staying at the same location allows the transmitter to use all its available energy in transmission, while moving to a new one may let the transmitter harvest higher amounts of energy and achieve higher rates at the expense of a cost incurred through the relocation process. We characterize this tradeoff optimally under both offline and online settings. Next, we consider different performance metrics, other than throughput, in energy harvesting communication networks. First, we study the issue of delay in single-user and broadcast energy harvesting channels. We define the delay per data unit as the time elapsed from the unit's arrival at the transmitter to its departure. With a pre-specified amount of data to be delivered, we characterize delay minimal energy management policies. We show that the structure of the optimal policy is different from throughput-optimal policies; to minimize the average delay, earlier arriving data units are transmitted using higher powers than later arriving ones, and the transmit power may reach zero, leading to communication gaps, in between energy or data arrival instances. Finally, we conclude this dissertation by considering the metric of the age of information in energy harvesting two-hop networks, where a transmitter is communicating with a receiver through a relay. Different from delay, the age of information is defined as the time elapsed since the latest data unit has reached the destination. We show that age minimal policies are such that the transmitter sends message updates to the relay just in time as the relay is ready to forward them to the receiver