Sabit Ekin

Achievable Capacity of a Spectrum Sharing System over Hyper Fading Channels

Cognitive radio with spectrum sharing feature is a promising technique to address the spectrum under-utilization problem in dynamically changing environments. In this paper, achievable capacity gain of spectrum sharing systems over dynamic fading environments is studied. For the analysis, a theoretical fading model called hyper fading model that is suitable to the dynamic nature of cognitive radio channel is proposed. Closed-form expression of probability density function (PDF) and cumulative density function (CDF) of the signal-to-noise ratio (SNR) for secondary users in spectrum sharing systems are derived. In addition, the capacity gains achievable with spectrum sharing systems in high and low power regions are obtained. Numerical simulations are performed to study the effects of different fading figures, average powers, interference temperature, and number of secondary users on the achievable capacity.

Performance of Cognitive Radios in Dynamic Fading Channels Under Primary Outage Constraint

This article investigates the performance of a cognitive user in a dynamic fading environment. The cognitive user communicates, using a spectrum-sharing technology, over a channel reserved to a primary user (PU). The transmit power of the cognitive user satisfies the outage probability constraint of the PU. The channels of the primary and cognitive users experience independent and non-identically distributed fading models. Nakagami-

Performance Analysis of Cognitive Radio Multiple-Access Channels Over Dynamic Fading Environments

m

Capacity of cognitive radio multiple-access channels in dynamic fading environments

m and hyper-Nakagami-

Capacity limits of spectrum-sharing systems over hyper-fading channels

m

Joint Decision of Sensing Threshold and Power Allocation in OFDM Cognitive Radio Networks

m channel fading models are specifically considered. The cognitive user’s mean transmit power, channel capacity, and bit error rate are derived for this setup. In addition, numerical results are presented to verify the theoretical analysis and investigate the effects of the parameters of the communication environment on the performance measures of the cognitive user.