This thesis introduces different mechanisms for energy efficiency in Wireless Sensor Networks (WSNs) along with maintaining high levels of Network Performance (N.P) with reduced complexity. Firstly, a Machine-to-Machine (M2M) WSN is arranged hierarchically in a fixed infrastructure to support a routing protocol for energy-efficient data transmission among terminal nodes and sink nodes via cluster heads (CHs). A Multi-Level Clustering Multiple Sinks (MLCMS) routing protocol with the IPv6 protocol over Low Wireless Personal Area Networks (6LoWPAN) is proposed to prolong network lifetime. The simulation results show 93% and 147% enhancement in energy efficiency and system lifespan compared to M-LEACH and LEACH, respectively. By utilising 6LoWPAN in the proposed system, the number of packets delivered increases by 7%, with higher accessibility to the M2M nodes and a substantial extension of the network is enabled. Secondly, an adaptive sleep mode with MLCMS for an efficient lifetime of M2M WSN is introduced. The time period of the active and asleep modes for the CHs has been considered according to a mathematical function. The evaluations of the proposed scheme show that the lifetime of the system is doubled and the end-to-end delay is reduced by half. Thirdly, enhanced N.P is achieved through linear integer-based optimisation. A Self-Organising Cluster Head to Sink Algorithm (SOCHSA) is proposed, hosting Discrete Particle Swarm Optimisation (DPSO) and Genetic Algorithm (GA) as Evolutionary Algorithms (EAs) to solve the N.P optimisation problem. N.P is measured based on load fairness and average ratio residual network energy. DPSO and GA are compared with the Exhaustive Search (ES) algorithm to analyse their performances for each benchmark problem. Computational results prove that DPSO outperforms GA regarding complexity and convergence, thus it is best suited for a proactive IoT network. Both algorithms achieved optimum N.P evaluation values of 0.306287 and 0.307731 in the benchmark problems P1 and P2, respectively, for two and three sinks. The proposed mechanism satisfies different N.P requirements of M2M traffic by instant identification and dynamic rerouting to achieve optimum performance. Finally, a Power Model (PM) is essential to investigate the power efficiency of a system. Hence, a Power Consumption (PC) profile for SDN-WISE, based on IoT is developed. The outcomes of the study offer flexibility in managing the structure of an M2M system in IoT. They enable controlling the provided Network Quality of Service (NQoS), precisely by achieving physical layer throughput. In addition, it provides a schematic framework for the Application Quality of Service (AQoS), specifically, the IoT data stream payload size (from the PC point of view). It is composed of two essential parts, i.e., control signalling and data traffic PCs and the results show a 98% PC of the data plane in the total system power, whereas the control plane PC is only 2%, with a minimum Transmission Time Interval (TTI) (5 sec) and a maximum payload size of 92 Bytes.

In this thesis, we focus on mobile networks consist of a single base station as the source transceiver, and multiple mobile stations as the receiving party. Applying energy management on multicasting between the base station and mobile stations, network users can conserve the energy consumed while wating for subscribing data contents to come. We referenced the SMBC-D (Scheduling over Multiple Broadcast Channels--the dynamic model) algorithm proposed by R. Cohen et al., grouping users with high request similarity, partitioning channels with a time-division duplexing scheme, and putting mobile stations into sleep mode during channels that include no subscribing data contents. Since SMBC-D statically schedules fixed size channels, groups request fewer data items will idle their channels after finishing their transmision, while groups request more data items take longer time to finish their transmission. For such problem, we propose a heuristic algorithm that makes use of these idle channels by combining adequate consecutive idle channels, to improve channel utility, and lower the overall energy consumed. We also process relevant computer simulations, verifying that our method has better performance.

An efficient design dedicated for iterative-multiple-input multiple-output (MIMO) receiver systems is now imperative in our world since data demands are increasing tremendously in wireless networks. This puts a massive burden on the signal processing power especially in small receiver systems where power sources are often shared or limited. This thesis proposes an attractive solution to both the wireless signal processing and the architectural implementation design sides of the problem. A novel algorithm, dubbed the Adaptive Switching Algorithm, is proven to not only save more than a third of the energy consumption in the algorithmic design, but is also able to achieve an energy reduction of more than 50% in terms of processing power when the design is mapped onto state-of-the-art programmable hardware. Simulations are based in MatlabTM using the Monte Carlo approach, where multiple additive white Gaussian noise (AWGN) and Rayleigh fading channels for both fast and slow fading environments were investigated. The software selects the appropriate detection algorithm depending on the current channel conditions. The design for the hardware is based on the latest field programmable gate arrays (FPGA) hardware from Xilinx R , specifically the Virtex-5 and Virtex-7 chipsets. They were chosen during the experimental phase to verify the results in order to examine trends for energy consumption in the proposed algorithm design. Savings come from dynamic allocation of the hardware resources by implementing power minimization techniques depending on the processing requirements of the system. Having demonstrated the feasibility of the algorithm in controlled environments, realistic channel conditions were simulated using spatially correlated MIMO channels to test the algorithm’s readiness for real-world deployment. The proposed algorithm is placed in both the MIMO detector and the iterative-decoder blocks of the receiver. When the final full receiver design setup is implemented, it shows that the key to energy saving lies in the fact that both software and hardware components of the Adaptive Switching Algorithm adopt adaptivity in the respective designs. The detector saves energy by selecting suitable detection schemes while the decoder provides adaptivity by limiting the number of decoding iterations, both of which are updated in real-time. The overall receiver can achieve more than 70% energy savings in comparison to state-of-the-art iterative-MIMO receivers and thus it can be concluded that this level of ‘intelligence’ is an important direction towards a more efficient iterative-MIMO receiver designs in the future.

It is widely accepted that low energy consumption is the most important requirement when designing components and systems for a wireless sensor network (WSN). The greatest energy consumer of each node within a WSN is the radio transceiver and as such, it is important that this component be used in an extremely energy e±cient manner. One method of reducing the amount of energy consumed by the radio transceiver is to turn it off and allow nodes to enter a sleep mode. The algorithms that directly control the radio transceiver are traditionally grouped into the Medium Access Control (MAC) layer of a communication protocol stack. This thesis introduces the emerging field of wireless sensor networks and outlines the requirements of a MAC protocol for such a network. Current MAC protocols are reviewed in detail with a focus on how they utilize this energy saving sleep mode as well as performance problems that they suffer from. A proposed new method of coordinating the use of this sleep mode between nodes in the network is specifed and described. The proposed new protocol is analytically compared with existing protocols as well as with some fundamental performance limits. The thesis concludes with an analysis of the results as well as some recommendations for future work.

A successive approximation register (SAR) circuit is adopted to control the digital delay line in the delay-locked loop (DLL) to achieve very fast locking effect in this proposed thesis. And in order to get low power consumption results, a loop state controller (LSC) is utilized to disable most of circuit. Because it is more easily to design and the advantages of high stability of delay-locked loop (DLL) compared to phase-locked loop (PLL), delay-locked loop (DLL) is more widely used in the adjustment of the clock error in the high frequency situation. This proposed delay locked loop (DLL) is added a register and a multiplexer in the feedback path. And the multiplexer does select which n-bit digital control code shall be read into the delay line; as the loop is locked, the path goes through the register is chosen to enter the sleep state ,and disable part of the circuit to make it into power saving mode. When entering the sleep state, the register provides the fixed input code; the phase error comparator (PEC) will keep tracking whether the frequency changes due to process, voltage, temperature and load (PVTL) variation uninterruptedly. Once there is something changed, the PEC will send a signal to inform the loop state controller (LSC) to enable the circuit from the sleep state, when the clock has to be locked again. And it just has 6 cycles time to relock, the lock range is form 150MHz to 900MHz. The power consuming are 15mW in lock mode and 9mW in sleep mode.

Data traffic demand has been increasing exponentially and this trend will continue over theforeseeable future. This has forced operators to upgrade and densify their mobile networks toenhance their capacity. Future networks will be characterized by a dense deployment of different kinds of base stations (BSs) in a hierarchical cellular structure. However network densification requires extensive capital and operational investment which limits operator revenues and raises ecological concerns over greenhouse gas emissions. Although networks are planned to support peak traffic, traffic demand is actually highly variable in both space and time which makes it necessary to adapt network energy consumption to inevitable variations in traffic demand. In this thesis, stochastic geometry tools are used to perform simple and tractable analysis of thecoverage, rate and energy performance of homogeneous networks and heterogeneous networks(HetNets). BSs in each tier are located according to independent Poisson Point Processes(PPPs) to generate irregular topologies that fairly resemble practical deployment topologies. The homogeneous network is optimized to determine the optimal BS density and transmit power configuration that minimizes its area power consumption (APC) subject to both coverage and average rate constraints. Results show that optimal transmit power only depends on the BSpower consumption parameters and can be predetermined. Furthermore, various sleep modemechanisms are applied to the homogeneous network to adapt its APC to changes in userdensity. A centralized strategic scheme which prioritize BSs with the least number of usersenhances energy efficiency (EE) of the network. Due to the complexity of such a centralizedscheme, a distributed scheme which implements the strategic algorithm within clusters of BSsis proposed and its performance closely matches that of its centralized counterpart. It is more challenging to model the optimal deployment configuration per tier in a multi-tier HetNet. Appropriate assumptions are used to determine tight approximations of these deployment configurations that minimize the APC of biased and unbiased HetNets subject tocoverage and rate constraints. The optimization is performed for three different user associationschemes. Similar to the homogeneous network, optimal transmit power per tier also depends onBS power consumption parameters only and can also be predetermined. Analysis of the effect of biasing on HetNet performance shows appropriate biasing can further reduce the deploymentconfiguration (and consequently the APC) compared to an unbiased HetNet. In addition, biasing can be used to offload traffic from congesting and high-power macro BSs to low-power small BSs. If idle BSs are put into sleep mode, more energy is saved and HetNet EE improves. Moreover, appropriate biasing also enhances the EE of the HetNet.

La consommation en énergie des réseaux de télécommunications a suscité un intérêt grandissant au cours des dernières années et les opérateurs mobiles cherchent des solutions innovantes pour optimiser l’efficacité énergétique. Dans cette thèse, nous nous focaliserons sur les schémas d’optimisation de la consommation d’énergie des réseaux d’accès mobiles. Nous commençons par étudier la stratégie de partage de charge qui minimise la consommation d’énergie dans la cellule tout en limitant l’impact sur la Qualité de Service. Le gain obtenu par ces algorithmes de gestion des ressources radio reste cependant limité; ceci est dû au fait que la consommation d’énergie ne dépend pas que de la charge, mais comporte une importante partie constante. Pour obtenir un gain plus important, nous proposons la mise en veille de certaines ressources du réseaux aux heures creuses où le trafic est faible, ce qui mène à des gains substantiels. Nous proposons ensuite un contrôleur de gestion de la mise en veille qui choisit l’action optimale en fonction de l’état du réseau. En effet, l’activation d’une nouvelle ressource n’est pas instantanée et un effet ping-pong peut apparaitre suite aux commandes simultanées d’activation/désactivation des ressources. Nous adaptons nos contrôleurs afin de prendre en compte ces imperfections, et nous montrons comment déduire la politique optimale. Nous étudions ensuite le cas de déploiement de petites cellules dans des réseaux hétérogènes et montrons que leur efficacité énergétique est améliorée par rapport au réseau purement macro-cellulaire, pourvu que la consommation d’énergie de petites cellules reste faible. Nous proposons ensuite un contrôleur optimal qui active/désactive les petites cellules en se basant sur des informations de trafic et de localisation des usagers. Nous considérons différents cas de figure avec une information complète, partielle ou retardée et montrons que ces schémas de mise en veille permettent d’atteindre d’importants gains de consommation d’énergie / In the recent years, more importance has been given to the energy consumption issue in telecommunication networks and mobile operators are rethinking their network design for optimizing its energy efficiency. In this thesis, we propose schemes for optimizing the energy consumption of mobile access networks. We begin by proposing energy-aware Radio Resource Management (RRM) schemes and show that a load balancing between available resources gives some energy savings. However, these gains remain small as a large part of the energy consumption is load-independent. We thus propose sleep mode schemes of resources in the network (cells or carriers) and show that they give a large gain when traffic is low. We then propose optimal sleep mode controllers that give, for each traffic scenario, the best actions to take in each state of the network. We make two observations: the first is that activating a new resource is not instantaneous, leading to QoS degradation if a conservative policy is not considered, and the second is that a ping-pong effect may appear at the frontier between two capacity regions. We adapt our controllers to take into account these imperfections, and show how to derive the optimal policy using Markov decision theory. We then extend our works to the case of small cell deployment in heterogeneous networks, composed of macro and small cells base stations. We study the capacity and power consumption of these networks and show that the energy efficiency is increased for some deployment strategies when the power consumption of small cells is low. We then propose sleep mode for small cells and develop optimal sleep/wakeup schemes based on the information on traffic load and user localization in the cell, in the cases where this information is complete, partial or delayed. We show that these sleep mode schemes achieve large energy consumption gains

This thesis proposes an implementation of battery-powered, time-synchronized wireless nodes that can be deployed in a wireless network topology. Wireless sensor networks are used in a wide variety of scenarios where emphasis is placed on the wireless nodes’ battery life. The main area of focus in this thesis is to examine how wireless nodes can save battery power by utilizing a deep sleep mode and wake up simultaneously using time synchronization to carry out their data communication. This was achieved by deploying five time-synchronized, battery-powered nodes in a wireless network topology. The difference in battery current draw between continuously running nodes and sleep-enabled nodes were measured, as well as the time duration needed by the nodes to successfully send their payloads and route other nodes’ data. The nodes needed between 1502 ms and 3273 ms on average to carry out their data communication, depending on where they were located in the network topology. Measurements show that sleep-enabled nodes on average draw substantially less current than continuously running nodes during a complete data communication cycle. When sleep-enabled nodes were powered by two AA batteries, an increase in battery life of up to 1800% was observed.

<p>Designing an application specific integrated circuit (ASIC) must be starting with careful preparations, otherwise the chip will not be as good as possible. The theoretical studies must cover everything from the chip circuits to the application structure. In mobile applications there is extremely important that the current consumption becomes minimized because the battery power is limited. The power reductions studies must include the most power costing circuits on the chip. When the whole circuit or segments of the circuit is not in use, they must switch fast and simple into another mode that consume nearly none power. This mode is called sleep-mode. If the sleep-mode has very low leakage currents, the lifetime of the application will dramatically increase. </p><p>This report studies the most power costing circuits in smartcard application ASIC. The chip should be used to control a LCD display on the smartcard. The circuits that have been investigated are level shifters, charge pumps and LCD drivers, also sleep-mode configuration possibilities have been investigated. Other small preparing work is also included in the thesis.</p>

Designing an application specific integrated circuit (ASIC) must be starting with careful preparations, otherwise the chip will not be as good as possible. The theoretical studies must cover everything from the chip circuits to the application structure. In mobile applications there is extremely important that the current consumption becomes minimized because the battery power is limited. The power reductions studies must include the most power costing circuits on the chip. When the whole circuit or segments of the circuit is not in use, they must switch fast and simple into another mode that consume nearly none power. This mode is called sleep-mode. If the sleep-mode has very low leakage currents, the lifetime of the application will dramatically increase. This report studies the most power costing circuits in smartcard application ASIC. The chip should be used to control a LCD display on the smartcard. The circuits that have been investigated are level shifters, charge pumps and LCD drivers, also sleep-mode configuration possibilities have been investigated. Other small preparing work is also included in the thesis.