Distributed discrete power control for bursty transmissions over wireless data networks

Transmitter power control has proven to be an efficient method to control cochannel interference in cellular PCS, and to increase bandwidth utilization. Power control can also improve channel quality, lower the power consumption, and facilitate network management functions such as mobile removals, hand-off and admission control. Most of the previous studies have assumed that the transmitter power level is controlled in a continuous domain, whereas in digitally power controlled systems, power levels are discrete. In this paper we study the transmitter power control problem using only a finite set of discrete power levels. The optimal discrete power vector is characterized, and a Distributed Discrete Power Control (DDPC) algorithm which converges to it, is presented. The impact of the power level grid on the outage probability is also investigated. A microcellular case study is used to evaluate the outage probabilities of the algorithms.

In this paper, we propose a novel energy efficient route construction scheme with transmission power control in ad hoc sensor networks. The proposed scheme is very simple and can improve energy consumption performance without any information of neighbor nodes. In the proposed scheme, when a node receives a route request (RREQ), the node calculates the standby time inversely proportional to the received power of the RREQ. The node relays the RREQ with full power when the standby time expires in order to construct the least energy consumption route. After the route construction, source and intermediate nodes transmit packets with power controlled medium access control (MAC) protocol. In addition, we propose the extended version of the proposed scheme to construct energy efficient route in discrete power control environment. Simulation results show the proposed scheme can construct more energy efficient route than the conventional schemes in both continuous and discrete power control environment.

Transmitter power control is an essential tool for managing the interference in a system constituted by a set of communications nodes. In the absence of a central controller, the decentralized power control is of special interest and may be characterized as a competition among the communication nodes. This indicates the adequacy of the application of noncooperative game theory concepts to the problem. The continuous domain for transmit power is usually assumed, although, in practice, digitally power controlled systems work with discrete power levels. In this work we evaluate the performance of a distributed power control algorithm which is derived from the formulation of the power control problem as a static multi-stage nonzero- sum noncooperative game. Continuous and discrete domains for transmit power are considered.

Most of the power control (PC) algorithms assumed that the link gains are fixed, and the power control command can take any value in the real field. These two assumptions are unrealistic in actual communication systems, since link gains are time varying and power control commands must be sent over capacity limited channels. In this paper, we propose a binary feedback power control algorithm (BFPC) for time-varying link gain environments. This algorithm can possibly be implemented as a 1-bit increase/decrease power control command, and we construct a connection between the link gains and the step-size of the proposed algorithm. It is shown that the proposed algorithm drives the CIR to an interval in time-varying link gain environments. Simulation results show that the proposed algorithm is more robust against link gains changes as compared to Foschini and Miljanic's distributed algorithm (FMA) and proportional power control algorithm (PropPC), and the proposed algorithm can be adopted in practical mobile communication systems.

It has been shown that power control is an efficient approacn to achieve me quality of service (QoS) requirement in wireless networks. In this letter, we present a utility function that denotes the QoS and energy efficiency of each wireless terminal. We propose a framework of power control based on the game theory for the QoS of wireless mesh networks (WMNs). In this framework, all players do their best to maximize their own utility. Furthermore, we present a Nash Equilibrium (NE) point of the power control game. We prove that the equilibrium is inefficient, and we propose a distributed power control algorithm that improves the total utility with respect to the NE point. Finally, the proposed framework is evaluated by a numerical experiment, the results of which show the rationality of our system model and the efficiency of our power control algorithm.

Optimizing spectral reuse is a major issue in large-scale IEEE 802.11 wireless networks. Power control is an effective means for doing so. Much previous work simply assumes that each transmitter should use the minimum transmit power needed to reach its receiver, and that this would maximize the network capacity by increasing spectral reuse. It turns out that this is not necessarily the case, primarily because of hidden nodes. In a network without power control, it is well known that hidden nodes give rise to unfair network bandwidth distributions and large bandwidth oscillations. Avoiding hidden nodes (by extending the carrier-sensing range), however, may cause the network to have lower overall network capacity. This paper shows that in a network with power control, reducing the instances of hidden nodes can not only prevent unfair bandwidth distributions, but also achieve higher overall network capacity compared with the minimum-transmit-power approach. We propose and investigate two distributed adaptive power control algorithms that minimize mutual interferences among links while avoiding hidden nodes. In general, our power control algorithms can boost the capacity of ordinary non-power-controlled 802.11 networks by more than two times while eliminating hidden nodes

Optimizing spectral reuse is a major issue in large-scale IEEE 802.11 wireless networks. Power control is an effective means for doing so. Much previous work simply assumes that each transmitter should use the minimum transmit power needed to reach its receiver, and that this would maximize the network capacity by increasing spectral reuse. It turns out that this is not necessarily the case, primarily because of hidden nodes. This paper shows that in a network with power control, avoiding hidden nodes can achieve higher overall network capacity compared with the minimum-transmit-power approach. It is not always best to use the minimum transmit powers even from the network capacity viewpoint. Specifically, we propose and investigate two distributed adaptive power control algorithms that minimize mutual interferences among links while avoiding hidden nodes. Different power control schemes have different numbers of exposed nodes and hidden nodes, which in turn result in different network capacities and fairness. Although there is usually a fundamental tradeoff between network capacity and fairness, we show that, interestingly, this is not always the case. In addition, our power control algorithms can operate at desirable network- capacity-fairness tradeoff points, and can boost the capacity of ordinary non-power-controlled 802.11 networks by two times while eliminating hidden nodes.

Transmitter adaptation in conjunction with power control enables individual users in multi-user wireless systems to meet specific quality of service (QoS) constraints imposed in terms of target values for the users' signal-to-interference+noise-ratio (SINR) at their intended receiver. Existing algorithms for joint transmitter adaptation and power control require knowledge of channel state information (CSI) which is in general difficult to acquire in wireless environments that are subject to fading. In this paper we study the performance of incremental algorithms for joint transmitter adaptation and power control with fading channels by formally defining a probability of outage measure and evaluating it through Monte-Carlo simulations in specific scenarios.

A major challenge in the operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With the increasing demand for wireless data services, it is necessary to establish power control algorithms for information sources other than voice. We present a power control solution for wireless data in the analytical setting of a game theoretic framework. In this context, the quality of service (QoS) a wireless terminal receives is referred to as the utility and distributed power control is a noncooperative power control game where users maximize their utility. The outcome of the game results in a Nash (1951) equilibrium that is inefficient. We introduce pricing of transmit powers in order to obtain Pareto improvement of the noncooperative power control game, i.e., to obtain improvements in user utilities relative to the case with no pricing. Specifically, we consider a pricing function that is a linear function of the transmit power. The simplicity of the pricing function allows a distributed implementation where the price can be broadcast by the base station to all the terminals. We see that pricing is especially helpful in a heavily loaded system.

Throughput and lifetime are usually conflicting objectives in designing wireless sensor networks; hence, the right balance needs to be found. With this aim in view, we address in this paper the problem of minimizing the frame length defined within a time division multiple access scheme and the problem of maximizing network lifetime subject to a maximum frame length. The pursued solution in either case leverages a wide range of parameters related to coverage, routing, transmission power, and data rate. Furthermore, it is consistent with the physical interference model. To this end, we rely on column generation technique to derive near‐optimal solutions even when the integrality constraints on coverage and flow variables are enforced. Moreover, we propose a polynomial‐time heuristic algorithm to solve efficiently the underlying NP‐hard problem of concurrent link selection with discrete power control and rate adaptation. Simulation results show that our heuristic algorithm leads to solutions within 3% of optimality while saving around 99% of computation time. Besides, the results illustrate the significant impact of power control and rate adaptation on throughput and lifetime improvement. Interestingly, we found that network lifetime can be significantly prolonged when traffic demands are sufficiently low at the affordable cost of small decrease in throughput. Copyright © 2015 John Wiley & Sons, Ltd.

A key issue in wireless multimedia networking regards the coexistence of different services/traffic types over common wireless resources. Research in Transmitter Power Control (TPC) has proposed various schemes for different traffic types without addressing effectively the problem of coexistence. Each of the TPC schemes of the literature is usually (i) unsuitable/inefficient for supporting diverse traffic types, and (ii) incompatible with each other, leading to conflicts if operated over common wireless channels.In this paper, we tackle the problem of coexistence by presenting novel converged TPC schemes. First, we investigate converged TPC schemes for links carrying the two basic traffic types of media streaming circuit-switched/constant-rate traffic (i.e. voice, CBR video), andpacket-switched elastic traffic (i.e. data).Evaluated against conventional TPC algorithms operating in dedicated wireless resources, the proposed schemes are demonstrated to increase the capacity of the wireless network. Second, we explore new hybrid types of traffic that combine the best-effort grade of service adapting to the network conditions with a guaranteed minimum, and propose appropriate TPC schemes.

The paradigm of wireless mesh networks has matured in the last decade after extensive research and development. As opposed to the time of their inception, current mesh networks are expected to deliver carrier-grade access services to their users. With the increasing expectations, it is generally recognized that there is a lack of understanding of the level of service continuity that mesh networks can provide to its users. In this research, we address a set of network design problems and propose solutions to improve the service continuity of wireless mesh networks. First, we investigate power control as a network layer problem in mesh networks. It is commonly acknowledged that reducing transmit power levels of nodes to the minimum required to retain connectivity always increases network capacity. In this work, we show that increasing power level of nodes can be beneficial in many cases depending on network’s traffic and topological characteristics. With extensive analysis and simulations, we characterize achievable spatial reuse and capacity with respect to power control in various practical scenarios. Second, we address the problem of generation of traffic hot-spots in wireless networks, and propose a novel power control scheme for load balancing. Using a heuristic based on the concept of centrality, we show that if we increase the power levels of only the nodes which are expected to relay more packets, significant relay load balancing can be achieved even using shortest path routing. Different from divergent routing schemes, such load balancing strategy is applicable to any arbitrary topology and traffic pattern. With this understanding of power control and load balancing, we investigate the service continuity issues of an urban-scale mesh networks. We define and study two essential service continuity metrics - connection robustness (K-center availability) and performance robustness (K-center performability). K-center availability is the fraction of the time a mesh network is available to its users, while performability is a composite measure of performance (here - throughput) and robustness that captures aggregate experience of mesh users over a long period of time. We develop efficient algorithms for estimating these quantities for large urban-scale meshes and study their characteristics in various existing mesh networks. Our study reveals numerous novel insights that can help in designing mesh networks with high availability and performability. While evaluating the performability, we used ideal case throughput performance estimation that ensures fair network resource allocation among the flows. Although this allows faster computation which is especially necessary for large state space exploration, it is difficult to implement in real-world using CSMA/CA MAC. To address this, we target the issue of unfair and lower utilization of network resources in wireless networks. Specifically, in a mesh network, nodes closer to gateways often achieve a larger share of bandwidth resources while nodes farther away often starve for useful bandwidth. Using back-pressure utility maximization framework, we provide a solution to the issue of spatial bias that can be implemented using current 802.11 standards. To further increase the efficiency of back-pressure policy in mesh networks, we propose a dynamic packet aggregation scheme that is especially effective in Internet-like packet size distribution. Along the same lines, we use the back-pressure invariants to develop a variable channel width assignment scheme that can yield maximum benefits of using varying-sized channels while remaining fair in network-wide resource allocation.

A major cause of energy waste in wireless networks is the interference between nodes working in the same frequency band. This problem appears to be more serious in Wireless Body Area Networks (WBANs) in which energy is the most valuable resource. In order to cope with this issue, power control techniques can be employed. Amongst potential approaches, those with intelligence which allow WBANs to improve their performance by learning from experience can remarkably increase flexibility and adaptability. Besides, approaches with less inter-node negotiation and cooperation are more attractive in WBANBs due to their low overhead and superior scalability. In this paper, we propose a power controller which employs Reinforcement Learning (RL) to enable WBANs to learn from experience and coordinate their power levels in a distributed manner with no inter-node negotiation and cooperation. We evaluate the performance of the proposed power controller with different RL algorithms and compare them to a counterpart approach based on game theory without learning. Their performances are evaluated in terms of optimality of the solution and convergence. We show that the RL-based power controller can trade off throughput for transmission power level and achieve lower energy consumption compared to the counterpart game.

This paper presents new distributed power and admission control algorithms for ad-hoc wireless networks in random channel environments. Previous work in this area has focused on distributed control for ad-hoc networks with fixed channels. We show that the algorithms resulting from such formulations do not accurately capture the dynamics of a time-varying channel. The performance of the network in terms of power consumption and generated interference can be severely degraded when power and admission control algorithms that are designed for deterministic channels are applied to random channels. In particular, some well-known optimality results for deterministic channels no longer hold. In order to address these problems we propose a new criterion for power optimality in ad-hoc wireless networks. We then show that the optimal power allocation for this new criterion can be found through an appropriate stochastic approximation algorithm. We also present a modified version of this algorithm for tracking nonstationary equilibria, which allows us to perform admission control. Ultimately, the iterations of the stochastic approximation algorithms can be decoupled to form fully distributed on-line power and admission control algorithms for ad-hoc wireless networks with time-varying channels.

This paper is concerned with the power control problem in wireless networks and presents bounded-input bounded-output (BIBO) stability analysis of the classic Foschini-Miljanic (FM) power control algorithm with logarithmic quantized feedback. Thereby, we first construct the model of FM algorithm with logarithmic quantized state feedback, where the feedback scheme has been used by multi-input system with imperfect input channels. Then we analyze BIBO stability of system and derive sufficient and necessary condition of the stability. Finally we provide numerical examples to demonstrate the correctness of condition and compare quantized effects under different parameters.