Discrete Power Control Research Articles

Joint Network Selection and Discrete Power Control in Heterogeneous MIMO Networks: A Game Theoretical Approach

Next-generation wireless networks will integrate multiple wireless access technologies and the users will access the network using one of several available radio access technologies. In this paper, we study the spectrum access problem in heterogeneous multipleinput multiple-output (MIMO) networks through a game theoretic approach. The spectrum access problem in the considered system model is defined as joint network selection and discrete power control. We formulate the problem as a noncooperative game where the players are the multi-mode terminals and. The proposed common utility function takes both transmission rate and the power consumption into account. This game is shown to be a potential game which possess at least one pure strategy Nash equilibrium (NE) and the optimal strategy profile which maximizes the total energy efficiency of the heterogeneous MIMO network constitutes a pure strategy NE of our proposed game. Furthermore, we prove that the price of anarchy of the proposed game is equal to 1. In order to achieve the pure strategy NE, we design an iterative spectrum access algorithm. The convergence and the complexity of our designed algorithm is discussed. It is shown that the designed algorithm can achieve optimal performance with low complexity.

Weighted Sum-Rate Maximization in Multi-Cell Networks via Coordinated Scheduling and Discrete Power Control

Inter-cell interference mitigation is a key challenge in the next generation wireless networks which are expected to use an aggressive frequency reuse factor and a high-density base station deployment to improve coverage and spectral efficiency. In this work, we consider the problem of maximizing the weighted sum-rate of a wireless cellular network via coordinated scheduling and discrete power control. We present two distributed iterative algorithms which require limited information exchange and data processing at each base station. Both algorithms provably converge to a solution where no base station can unilaterally modify its status (i.e., transmit power and user selection) to improve the weighted sum-rate of the network. Numerical studies are carried out to assess the performance of the proposed schemes in a realistic system based on the IEEE 802.16m specifications. Simulation results show that the proposed algorithms achieve a significant rate gain over uncoordinated transmission strategies for both cell-edge and inner users.

Dynamic Discrete Power Control in Cellular Networks

We consider an uplink power control problem where each mobile wishes to maximize its throughput (which depends on the transmission powers of all mobiles) but has a constraint on the average power consumption. A finite number of power levels are available to each mobile. The decision of a mobile to select a particular power level may depend on its channel state. We consider two frameworks concerning the state information of the channels of other mobiles: i) the case of full state information and ii) the case of local state information. In each of the two frameworks, we consider both cooperative as well as non-cooperative power control. We manage to characterize the structure of equilibria policies and, more generally, of best-response policies in the non-cooperative case. We present an algorithm to compute equilibria policies in the case of two non-cooperative players. Finally, we study the case where a malicious mobile, which also has average power constraints, tries to jam the communication of another mobile. Our results are illustrated and validated through various numerical examples.

A 2.4 GHz Fully Integrated Linear CMOS Power Amplifier With Discrete Power Control

A fully integrated 2.4 GHz CMOS power amplifier (PA) in a standard 0.18 mum CMOS process is presented. Using a parallel-combining transformer (PCT) and gate bias adaptation, a discrete power control of the PA is achieved for enhancing the efficiency at power back-off. With a 3.3 V power supply, the PA has a peak drain efficiency of 33% at 31 dBm peak output power. By applying discrete power control, a reduction of 650 mA in current consumption can be achieved over the low output power range while satisfying the EVM requirements of WLAN 802.11g and WiMAX 802.16e signals.

On game-theoretic power control under successive interference cancellation

Game-theoretic analytical techniques have been applied, of late, to uplink power control in DS-CDMA networks. We extend our previous analysis [1] of game-theoretic power control under successive interference cancellation performed under a dynamic cancellation ordering. Both continuous and discrete power control are investigated. Under continuous power control, we prove the nonexistence of a symmetric power control equilibrium, illustrating that no easily applicable equilibrium existence result applies to this power control problem. Under discrete power control, we demonstrate empirically a high probability of equilibrium if the action set is not too precise, an encouraging result in the absence of a pure-strategy equilibrium guarantee.

Stochastic Learning Solution for Distributed Discrete Power Control Game in Wireless Data Networks

Distributed power control is an important issue in wireless networks. Recently, noncooperative game theory has been applied to investigate interesting solutions to this problem. The majority of these studies assumes that the transmitter power level can take values in a continuous domain. However, recent trends such as the GSM standard and Qualcomm's proposal to the IS-95 standard use a finite number of discretized power levels. This motivates the need to investigate solutions for distributed discrete power control which is the primary objective of this paper. We first note that, by simply discretizing, the previously proposed continuous power adaptation techniques will not suffice. This is because a simple discretization does not guarantee convergence and uniqueness. We propose two probabilistic power adaptation algorithms and analyze their theoretical properties along with the numerical behavior. The distributed discrete power control problem is formulated as an N-person, nonzero sum game. In this game, each user evaluates a power strategy by computing a utility value. This evaluation is performed using a stochastic iterative procedures. We approximate the discrete power control iterations by an equivalent ordinary differential equation to prove that the proposed stochastic learning power control algorithm converges to a stable Nash equilibrium. Conditions when more than one stable Nash equilibrium or even only mixed equilibrium may exist are also studied. Experimental results are presented for several cases and compared with the continuous power level adaptation solutions.

Signal Strength Based Energy Efficient Routing for Ad Hoc Networks

In this paper, we propose a novel energy-efficient route-discovery scheme with transmission power control (TPC) for ad hoc networks. The proposed scheme is very simple and improves energy efficiency without any information about neighbor nodes. In the proposed scheme, when a node receives a route request (RREQ), the node calculates the routing-level backoff time as being inversely proportional to the received power of the RREQ. After the route discovery, source and intermediate nodes transmit packets by the power-controlled medium access control (MAC) protocol. In addition, we propose an extended version of the proposed scheme for discrete power control devices. Simulation results demonstrate the proposed schemes can discover more energy efficient routes than the conventional schemes.

Distributed Discrete Power Control in Cellular PCS

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.