Continuous Power Adaptation Research Articles

Statistical CSI Driven Transmit Antenna Selection and Power Adaptation in Underlay Spectrum Sharing Systems

In underlay spectrum sharing, transmit antenna selection (TAS) improves the performance of a secondary system and helps it control the interference it causes to a primary system. TAS does so with a hardware complexity and cost comparable to a single antenna system. We present a novel and optimal joint TAS and continuous power adaptation rule for a practically relevant, less explored model in which the secondary transmitter knows only the statistics of channel gains from itself to one or more primary receivers. The rule minimizes the average symbol error probability (SEP) of the secondary system for an entire class of stochastic interference constraints. This general class subsumes the average interference constraint and its novel generalization, and the interference-outage constraint. We derive closed-form expressions for the transmit power and selected antenna. We then develop a general analysis of the optimal average SEP that applies to several widely-used fading models. We also present computationally-efficient approaches to determine the parameters that specify the optimal rule. Our comprehensive numerical results characterize the very different impacts of the interference constraint on both secondary and primary systems. They show that the optimal rule reduces the average SEP by two orders of magnitude compared to conventional approaches.

Statistical Energy Efficiency Characterization for Wireless Transmission Over Fading Channels

Future Internet of Things (IoT) applications demand highly energy-efficient wireless transmission solutions. In this article, we characterize the energy efficiency (EE) of wireless transmission over fading channels from individual transmission session perspective. Specifically, we apply a statistical EE metric to analyze and optimize ideal continuous rate adaptation (CRA) and continuous power adaptation (CPA) transmission schemes. The resulting statistical characterization establishes an EE performance limit for data transmissions over fading channels and facilitates a direct tradeoff analysis between maximal achievable EE and instantaneous latency requirement.

Asymptotic Performance Analysis of Generalized User Selection for Interference-Limited Multiuser Secondary Networks

We analyze the asymptotic performance of a generalized multiuser diversity scheme for an interference-limited secondary multiuser network of underlay cognitive radio systems. Assuming a large number of secondary users and that the noise at each secondary user's receiver is negligible compared to the interference from the primary transmitter, the secondary transmitter transmits information to the $k$-th best secondary user, namely, the one with the $k$-th highest signal-to-interference ratio (SIR). We use extreme value theory to show that the $k$-th highest SIR converges uniformly in distribution to an inverse gamma random variable for a fixed $k$ and large number of secondary users. We use this result to derive asymptotic expressions for the average throughput, effective throughput, average bit error rate and outage probability of the $k$-th best secondary user under continuous power adaptation at the secondary transmitter, which ensures satisfaction of the instantaneous interference constraint at the primary receiver caused by the secondary transmitter. Numerical simulations show that our derived asymptotic expressions are accurate for different values of system parameters.

New transmission scheme to enhance throughput of DF relay network using rate and power adaptation

ABSTRACTThis paper presents a new transmission scheme for a decode and forward (DF) relay network using continuous power adaptation while independent average power constraints are provisioned for each node. To have analytical insight, the achievable throughputs are analysed using continuous adaptation of the rates and the powers. As shown by numerical evaluations, a considerable outperformance is seen by continuous power adaptation compared to the case where constant powers are utilised. Also for practical systems, a new throughput maximised transmission scheme is developed using discrete rate adaptation (adaptive modulation and coding) and continuous transmission power adaptation. First a 2-hop relay network is considered and then the scheme is extended for an N-hop network. Numerical evaluations show the efficiency of the designed schemes.

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.

Rate and Power Allocation for Discrete-Rate Link Adaptation

Link adaptation, in particular adaptive coded modulation (ACM), is a promising tool for bandwidth-efficient transmission in a fading environment. The main motivation behind employing ACM schemes is to improve the spectral efficiency of wireless communication systems. In this paper, using a finite number of capacity achieving component codes, we propose new transmission schemes employing constant power transmission, as well as discrete- and continuous-power adaptation, for slowly varying flat-fading channels. We show that the proposed transmission schemes can achieve throughputs close to the Shannon limits of flat-fading channels using only a small number of codes. Specifically, using a fully discrete scheme with just four codes, each associated with four power levels, we achieve a spectral efficiency within 1 dB of the continuous-rate continuous-power Shannon capacity. Furthermore, when restricted to a fixed number of codes, the introduction of power adaptation has significant gains with respect to average spectral efficiency and probability of no transmission compared to a constant power scheme.