Energy Efficient Inverse Power Control for a Cognitive Radio Link Marko Höyhtyä 1 , Anant Sahai 2 , Danijela Cabric 2 , and Aarne Mämmelä 1 1 VTT Technical Research Centre of Finland 2 Berkeley Wireless Research Center P.O. Box 1100, FI›90571 Oulu University of California, CA 94704 Finland USA Abstract—In this paper, a novel adaptive energy and spectrum efficient inverse power control method that is based on the truncated filtered›x LMS (FxLMS) algorithm is introduced. By truncated power control we mean power control where transmission is interrupted if the channel state deteriorates to bad enough. Inverse power control minimizes the interference that a cognitive radio (CR) creates to licensed users and allows more users to share the spectrum. To further reduce the transmission power and consequently the interference, truncation in power control is used. The performance of the system is improved and the amount of needed transmitted energy is smaller. Based on numerical analysis this new method offers energy efficient transmission, helps to minimize interference to the primary users, and allows even more users to share the same spectrum. Keywords›FxLMS algorithm; truncated power control; interference control; I. INTRODUCTION Spectral efficiency plays a key role as future wireless communication systems will accommodate more and more users and high performance services. Nowadays the spectrum is used inefficiently. Cognitive radio technologies have been proposed to improve the spectral efficiency [1], [2]. The aim of cognitive radio system is very practical and concentrates on the efficient use of natural resources, which include frequency, time, and transmitted energy. Spectrum awareness is a key requirement for a CR to operate [3]. However, dynamic spectrum management and power control are equally important functions as spectrum sensing. It is important to know how detected spectrum holes can be efficiently exploited while assuring the minimal interference to the primary users (PU) as well as to the other cognitive networks that share the same spectrum. Transmission parameters have to be adapted based on the sensed spectrum and the channel estimation. Inside the net, interference can be controlled with orthogonality principles whereas interference to the other networks is mainly controlled by reducing the transmitter power to the minimum. Because of interference, the cognitive radios have to adjust their power levels according to their potential proximity to a primary receiver [4]. In [5] the task of power control is presented as “to permit transmission at full power limits when necessary, but constrain the transmitter power to a lower level to allow greater sharing of spectrum when higher power operation is not necessary”. In active cognitive radio system, secondary users (SU) actively sense the surrounding radio environment and adapt their transmission based on the measurements. Spectrum sensing sensitivity can be used to calculate the potential proximity to the primary receiver and to estimate the power limit for secondary transmission. Given this power limit for transmission, can we use conventional adaptive power control methods to cope with multipath fading in a CR system? How can we efficiently use available spectral and energy resources and reduce interference to primary users and other secondary users sharing the same spectrum? What are the actual interference ranges of our own system? This paper addresses these questions, proposes a method for calculation of power limit and introduces a novel FxLMS algorithm based method to be used for power control over a cognitive link. A very conventional approach for transmitter power control is to maintain desired signal strength at the receiver by inverting the channel power gain based on the channel estimates. Delay›sensitive applications require full inversion methods to be used in power control. However, in a cognitive radio network using active awareness principles, delays cannot be avoided because of periodical sensing. Such a network is not good for real›time communication. Thus, power control method does not need to assure delayless communication. A large part of the transmission power in continuous inverse control solutions is used to compensate the deepest fades in a fading channel. For energy or power efficiency, threshold policies have to be used. It has been recently proven in [6] that regardless of modulation and demodulation methods and taken general assumptions in wireless channel model into account, the optimal power control method is based on threshold policy. Power efficiency and throughput can be clearly improved when compared to continuous transmission schemes. Link budget is an estimation technique for evaluating communication system performance [7]. The required bit error rate (BER) dictates the value of received signal›to›noise ratio (SNR) in order to meet that performance. In link budget calculations transmitter power, gains, and losses in the link are calculated with primary purpose of determination of actual operation point in the BER curve. However, conventional link budget calculations do not take effects of transmitter power control into account. We have shown in [8] that power control can improve or deteriorate the link budget depending on what kind of power control is used. Bit error rate depends both on the link budget and the distribution of the received signal. This work has been performed in the framework of the project CHESS, which is partly funded by TEKES.