Implementation of a Reconfiguration Algorithm for Cognitive Radio

Abstract

Abstract-In wireless communication systems, advances in computer architecture and processor technology have made it possible for functionality previously implemented in hardware to become tunable via software. These software-defined radios (SDRs) will allow new radio devices to sense, reason, and adapt to changes in the RF environment and/or application requirements making them cognitive radios (CRs). Fully exploiting the flexibility of cognitive radios, however, requires an understanding of how different permutations of radio parameters impact applicationspecific performance metrics. For example, a CR that is not meeting its bit loss goals could change its operating frequency to reduce the impact of interference. However, the added overhead from changing frequencies could result in an application failing its latency requirements. This paper describes one such method for configuring a cognitive radio and demonstrates the efficacy of the technique on both a simulation based analysis and an in situ evaluation on a software radio platform. Our reconfiguration system quantifies the influence of radio parameters such as frequency agility, bit rate, and transmit power for adapting communication at the application, medium access control, and physical layers. The method calls for exhaustively evaluating a set of CR configurations against a variety of performance metrics and applying statistical processes to determine which settings will have the most significant impact on performance. Once this is done, the experimental results are then used to inform the design of an algorithm that is able to reconfigure to meet performance goals. We show that while the method for deriving the model functions consistently across both the simulation and implementation platforms, the different evaluation platforms emphasize different parameters when controlling the radios.

Reconfiguration decision making in cognitive wireless network

“…Many recent proposals rely on multifarious technologies, such as design of experiment (DOE) [9][10][11], and seem to be well suited to handling large sets of multi-domain variables and carrying out reconfiguration decision for selecting the configuration meeting specified design objectives. However, a major drawback of this technique is that it is too computationally intensive.…”

Tunable Filter-Antennas for Cognitive Radio Applications

“…Cooperative sensing, whether it is centralized or distributed, is also proposed in [2,3], as a solution to problems that arise in spectrum sensing due to noise uncertainty, fading, and shadowing. The implementation of a reconfigurable sensing methodology [6], may adjust itself to minimize the probability of wrongful detection. Thus, a reconfigurable sensing methodology may constitute an optimal spectrum sensing solution.…”