Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches

An overview of game-theoretic approaches to energy-efficient resource allocation in wireless networks is presented. Focusing on multiple-access networks, it is demonstrated that game theory can be used as an effective tool to study resource allocation in wireless networks with quality-of-service (QoS) constraints. A family of non-cooperative (distributed) games is presented in which each user seeks to choose a strategy that maximizes its own utility while satisfying its QoS requirements. The utility function considered here measures the number of reliable bits that are transmitted per joule of energy consumed and, hence, is particulary suitable for energy-constrained networks. The actions available to each user in trying to maximize its own utility are at least the choice of the transmit power and, depending on the situation, the user may also be able to choose its transmission rate, modulation, packet size, multiuser receiver, multi-antenna processing algorithm, or carrier allocation strategy. The best-response strategy and Nash equilibrium for each game is presented. Using this game-theoretic framework, the effects of power control, rate control, modulation, temporal and spatial signal processing, carrier allocation strategy and delay QoS constraints on energy efficiency and network capacity are quantified.Comment: To appear in the IEEE Signal Processing Magazine: Special Issue on Resource-Constrained Signal Processing, Communications and Networking, May 200

The Bus Goes Wireless: Routing-Free Data Collection with QoS Guarantees in Sensor Networks

Abstract—We present the low-power wireless bus (LWB), a new communication paradigm for QoS-aware data collection in lowpower sensor networks. The LWB maps all communication onto network floods by using Glossy, an efficient flooding architecture for wireless sensor networks. Therefore, unlike current solutions, the LWB requires no information of the network topology, and inherently supports networks with mobile nodes and multiple data sinks. A LWB prototype implemented in Contiki guarantees bounded end-to-end communication delay and duplicate-free, inorder packet delivery—key QoS requirements in many control and mission-critical applications. Experiments on two testbeds demonstrate that the LWB prototype outperforms state-of-theart data collection and link layer protocols, in terms of reliability and energy efficiency. For instance, we measure an average radio duty cycle of 1.69 % and an overall data yield of 99.97 % in a typical data collection scenario with 85 sensor nodes on Twist. I

Energy Efficient Routing With Unreliable Links in Wireless Networks

Abstract — Energy efficient routings and power control techniques in wireless networks have drawn considerable research interests recently. In this paper, we address the problem of energy efficient reliable routing in wireless networks in the presence of unreliable communication links or devices or lossy wireless link layers by integrating the power control techniques into the energy efficient routing. We study both the case when the link layer implements a perfect reliability and the case when the reliability is implemented through the transport layer, e.g., TCP. We study the energy efficient unicast and multicast when the links are unreliable. Subsequently, we study how to perform power control (thus, controlling the reliability of each communication link) such that the unicast routings use the least power when the communication links are unreliable while the power used by multicast is close to optimum. We presented both centralized algorithms and distributed algorithms for all the questions we studied. We conducted extensive simulations to study the power consumption, the end-to-end delay, and the network throughput of our protocols compared with existing protocols. I

Wireless Information Transfer with Opportunistic Energy Harvesting

Energy harvesting is a promising solution to prolong the operation of energy-constrained wireless networks. In particular, scavenging energy from ambient radio signals, namely wireless energy harvesting (WEH), has recently drawn significant attention. In this paper, we consider a point-to-point wireless link over the narrowband flat-fading channel subject to time-varying co-channel interference. It is assumed that the receiver has no fixed power supplies and thus needs to replenish energy opportunistically via WEH from the unintended interference and/or the intended signal sent by the transmitter. We further assume a single-antenna receiver that can only decode information or harvest energy at any time due to the practical circuit limitation. Therefore, it is important to investigate when the receiver should switch between the two modes of information decoding (ID) and energy harvesting (EH), based on the instantaneous channel and interference condition. In this paper, we derive the optimal mode switching rule at the receiver to achieve various trade-offs between wireless information transfer and energy harvesting. Specifically, we determine the minimum transmission outage probability for delay-limited information transfer and the maximum ergodic capacity for no-delay-limited information transfer versus the maximum average energy harvested at the receiver, which are characterized by the boundary of so-called "outage-energy" region and "rate-energy" region, respectively. Moreover, for the case when the channel state information (CSI) is known at the transmitter, we investigate the joint optimization of transmit power control, information and energy transfer scheduling, and the receiver's mode switching. Our results provide useful guidelines for the efficient design of emerging wireless communication systems powered by opportunistic WEH.Comment: to appear in IEEE Transactions on Wireless Communicatio

multimedia transmission over wireless networks: performance analysis and optimal resource allocation

In recent years, multimedia applications such as video telephony, teleconferencing, and video streaming, which are delay sensitive and bandwidth intensive, have started to account for a significant portion of the data traffic in wireless networks. Such multimedia applications require certain quality of service (QoS) guarantees in terms of delay, packet loss, buffer underflows and overflows, and received multimedia quality. It is also important to note that such requirements need to be satisfied in the presence of limited wireless resources, such as power and bandwidth. Therefore, it is critical to conduct a rigorous performance analysis of multimedia transmissions over wireless networks and identify efficient resource allocation strategies. Motivated by these considerations, in the first part of the thesis, performance of hierarchical modulation-based multimedia transmissions is analyzed. Unequal error protection (UEP) of data transmission using hierarchical quadrature amplitude modulation (HQAM) is considered in which high priority (HP) data is protected more than low priority (LP) data. In this setting, two different types of wireless networks are considered. Specifically, multimedia transmission over cognitive radio networks and device-to-device (D2D) cellular wireless networks is addressed. Closed-form bit error rate (BER) expressions are derived and optimal power control strategies are determined. Next, throughput and optimal resource allocation strategies are studied for multimedia transmission under delay QoS and energy efficiency (EE) constraints. A Quality-Rate (QR) distortion model is employed to measure the quality of received video in terms of peak signal-to-noise ratio (PSNR) as a function of video source rate. Effective capacity (EC) is used as the throughput metric under delay QoS constraints. In this analysis, four different wireless networks are taken into consideration: First, D2D underlaid wireless networks are addressed. Efficient transmission mode selection and resource allocation strategies are analyzed with the goal of maximizing the quality of the received video at the receiver in a frequency-division duplexed (FDD) cellular network with a pair of cellular users, one base station and a pair of D2D users under delay QoS and EE constraints. A full-duplex communication scenario with a pair of users and multiple subchannels in which users can have different delay requirements is addressed. Since the optimization problem is not concave or convex due to the presence of interference, optimal power allocation policies that maximize the weighted sum video quality subject to total transmission power level constraint are derived by using monotonic optimization theory. The optimal scheme is compared with two suboptimal strategies. A full-duplex communication scenario with multiple pairs of users in which different users have different delay requirements is addressed. EC is used as the throughput metric in the presence of statistical delay constraints since deterministic delay bounds are difficult to guarantee due to the time-varying nature of wireless fading channels. Optimal resource allocation strategies are determined under bandwidth, power and minimum video quality constraints again using the monotonic optimization framework. A broadcast scenario in which a single transmitter sends multimedia data to multiple receivers is considered. The optimal bandwidth allocation and the optimal power allocation/power control policies that maximize the sum video quality subject to total bandwidth and minimum EE constraints are derived. Five different resource allocation strategies are investigated, and the joint optimization of the bandwidth allocation and power control is shown to provide the best performance. Tradeoff between EE and video quality is also demonstrated. In the final part of the thesis, power control policies are investigated for streaming variable bit rate (VBR) video over wireless links. A deterministic traffic model for stored VBR video, taking into account the frame size, frame rate, and playout buffers is considered. Power control and the transmission mode selection with the goal of maximizing the sum transmission rate while avoiding buffer underflows and overflows under transmit power constraints is exploited in a D2D wireless network. Another system model involving a transmitter (e.g., a base station (BS)) that sends VBR video data to a mobile user equipped with a playout buffer is also adopted. In this setting, both offline and online power control policies are considered in order to minimize the transmission power without playout buffer underflows and overflows. Both dynamic programming and reinforcement learning based algorithms are developed

Algorithmic Aspects of Energy-Delay Tradeoff in Multihop Cooperative Wireless Networks

We consider the problem of energy-efficient transmission in delay constrained cooperative multihop wireless networks. The combinatorial nature of cooperative multihop schemes makes it difficult to design efficient polynomial-time algorithms for deciding which nodes should take part in cooperation, and when and with what power they should transmit. In this work, we tackle this problem in memoryless networks with or without delay constraints, i.e., quality of service guarantee. We analyze a wide class of setups, including unicast, multicast, and broadcast, and two main cooperative approaches, namely: energy accumulation (EA) and mutual information accumulation (MIA). We provide a generalized algorithmic formulation of the problem that encompasses all those cases. We investigate the similarities and differences of EA and MIA in our generalized formulation. We prove that the broadcast and multicast problems are, in general, not only NP hard but also o(log(n)) inapproximable. We break these problems into three parts: ordering, scheduling and power control, and propose a novel algorithm that, given an ordering, can optimally solve the joint power allocation and scheduling problems simultaneously in polynomial time. We further show empirically that this algorithm used in conjunction with an ordering derived heuristically using the Dijkstra's shortest path algorithm yields near-optimal performance in typical settings. For the unicast case, we prove that although the problem remains NP hard with MIA, it can be solved optimally and in polynomial time when EA is used. We further use our algorithm to study numerically the trade-off between delay and power-efficiency in cooperative broadcast and compare the performance of EA vs MIA as well as the performance of our cooperative algorithm with a smart noncooperative algorithm in a broadcast setting.Comment: 12 pages, 9 figure

Improved Energy and Latency Efficient MAC Scheme for Dense Wireless Sensor Networks

The sensor nodes in the wireless sensor networks have limited battery power, which motivates to work on energy conserved MAC schemes for better lifetime and latency efficient. Previous work carried out in energy conserved MAC schemes are limit the idle listening time, reduces overhearing (sensor node hear a packet destined for other nodes) and minimizing the used control packet size. The current existing work presented ELE-MAC (i.e. Energy Latency Efficient MAC) which adopts less control packets to preserve energy in sparsely distributed sensor nodes of the wireless sensor networks. It performs statistically the same or better latency characteristic compared to adaptive SMAC. ELE-MAC follows the adaptive listening technique, which reduce the sleep delay introduced by the periodic sleep of each node in case of a multi-hops network. The proposal in this work, extends the ELE-MAC to work efficiently with wireless sensor network comprises of high node density by combining the RTS and SYNC control packets. The extended version uses two separate frequencies for data and control packets to avoid the use of handshake mechanisms (e.g. RTS/CTS) in order to reduce energy consumption and packet delay. It enables a receiver to send a busy tone signal on th control channel and notify the neighbors about the ongoing reception of data in progress. This process avoids packet collisions and in turn improves the node lifetime and throughput. The nodes in a sensor network have their own different traffic loads according to the tasks assigned and their locations. The extension of ELE MAC adopts the different traffic loads of each node as performance metric for reducing the latency. Each sensor node calculates its utilization after the last synchronization time, and adjusts its duty cycle according to the calculated utilization, and then send new schedule to its neighbors via broadcasting

Energy Efficiency of Wireless Access - Impact of Power Amplifiers and Load Variations

In order to ensure seamless coverage and sustainable exponential growth of capacity, there is a keen interest in the development and deployment of highly energy efficient wireless systems and solutions. To design an energy efficient network, it is important to consider the facts that the variations in traffic demand in both temporal and spatial domains are significant, and the power consumption of cellular networks is mostly dominated by macro base stations where the power amplifiers (PAs) consume around 55-70 percent of total energy. One of the main challenges lies in coping with this load variations considering that the PAs attain high efficiency only at around the maximum output power level. In this thesis, we propose energy efficient system level solutions for wireless access network that consider the non-ideal efficiency characteristics of the PA and the load variations.  We model and incorporate the PA efficiency in the energy-delay trade-off present in Shannon's channel capacity model in order to investigate the energy saving potential in a wireless access network at the cost of additional flow-level delay. We propose a best response iteration based distributed power control algorithm where the cells identify the power levels for different user locations to minimize energy consumption under delay constraints. We observe that energy saving potential strongly depends on the network load and PA efficiency characteristics. We also investigate the impact of additional delay in the downlink on the energy consumption of the mobile terminal.  Heterogeneous network is the leading technology for the next-generation cellular networks. We investigate the energy-efficient densification and load sharing between the layers of a heterogeneous network while taking into consideration the PA efficiency and temporal load variations (TLV). We also study the impact of PA efficiency and energy-delay trade-off on the energy efficient network densification.  Massive MIMO (MM) is another leading candidate technology to cater for very high capacity demand. We consider a multi-cell MM system and provide the guidelines to dimension the PA for the antennas. We also develop energy efficient antenna adaptation schemes that allow the cells to dynamically adapt the number of antennas to the TLV in order to maintain high energy efficiency (EE) throughout the day. Our results indicate that these proposed antenna adaptation schemes can improve the EE significantly