Opportunistic Spectrum Access

Cognitive radio (CR) technology is an innovative radio design philosophy in order to increase the spectrum utilization by exploiting the unused spectrum in dynamically changing environments. Specifically, the CR technology will allow a group of potential users (referred to as secondary users) to access available spectrum resources unused by primary users (PUs) for whom the band has been licensed. The spectrum available for secondary users (SUs) depends on PUs' activity in the licensed spectrum. In this paper, we develop a queuing analytic framework to study important performance measures experienced by SUs in a CR network. We study queuing delay and buffer statistics of SUs' packets by modeling PUs' activity as a two state Markov chain and SUs' channel quality variation as a finite state Markov chain (FSMC). In order to allocate available channels among the SUs, an opportunistic channel allocation scheme is considered. The proposed framework facilitates to design an admission controller for SUs' network in order to maintain a given quality service (QoS) requirement which is specified in the form of statistical delay guarantee.

The need to minimize resources and infrastructure for measuring electric power, water supply, etc., gives opening to an advanced metering infrastructure (AMI), more efficient automated systems to minimize costs and infrastructure. Runtime proposals must address the measurement systems today, get scalability and sustainability over time through the reuse of the blanks of the television band is addressed in the investigation, as this can be applied to mobile devices of cognitive radio. It provides benefits to apply this type of propagation considering cups use of frequency bands in the new metering infrastructure. Implement an algorithm to ensure a better allocation of spectrum, based on meta-programming methods based on heuristic selection events previously given. An initial set of objective functions which are real and viable solution to that particular point, provides a feasible solution. The availability, planning the allocation of channels and solutions for different scenarios predict loads of homogeneous and heterogeneous traffic. Applying the study in rural areas without much concentration index increased use buildings where spectrum is obtained by implementing micro-generation projects low scale

Cognitive radio (CR) is a revolutionary technology in wireless communications that enhances spectrum utilization by allowing opportunistic and dynamic spectrum access. One of the key challenges in this domain is how CR users cooperate to dynamically access the available spectrum opportunities in order to maximize the overall perceived throughput. In this paper, we consider the coordinated spectrum access problem in a multi-user single-transceiver CR network (CRN), where each CR user is equipped with only one half-duplex transceiver. We first formulate the dynamic spectrum access as a rate/power control and channel assignment optimization problem. Our objective is to maximize the sum-rate achieved by all contending CR users over all available spectrum opportunities under interference and hardware constraints. We first show that this problem can be formulated as a mixed integer nonlinear programming (MINLP) problem that is NP-hard, in general. By exploiting the fact that actual communication systems have a finite number of available channels, each with a given maximum transmission power, we transfer this MINLP into a binary linear programming problem (BLP). Due to its integrality nature, this BLP is expected to be NP-hard. However, we show that its constraint matrix satisfies the total unimodularity property, and hence our problem can be optimally solved in polynomial time using linear programming (LP). To execute the optimal assignment in a distributed manner, we then present a distributed CSMA/CA-based random access mechanism for CRNs. We compare the performance of our proposed mechanism with reference CSMA/CA channel access mechanisms designed for CRNs. Simulation results show that our proposed mechanism significantly improves the overall network throughput and preserves fairness.

This paper investigates the performance of a cognitive radio transceiver that can monitor multiple channels and opportunistically use any one of them should it be available. In our work, we propose and compare two different opportunistic channel access schemes. The first scheme applies when the secondary user (SU) has access to only one channel. The second scheme applies when the SU has access to multiple channels but can at a given time monitor and access only one channel. Two switching strategies, namely the ...

We consider a scenario in which frequency agile radios opportunistically share a fixed spectrum resource with a set of primary nodes. We develop a collaborative scheme for a group of frequency agile radios to estimate the maximum power at which they can transmit on a given frequency channel, without causing harmful interference to the primary receivers. The proposed scheme relies on signal strength measurements taken by a group of frequency agile radios, which are then used by a target node to characterize the spatial size of its perceived spectrum hole in terms of the maximum permissible transmit power. We derive an approximation to the maximum interference-free transmit power using the Cramer-Rao bound on localization accuracy. We focus on the case of a single transmitter, but briefly discuss how the proposed approach can extend to more general situations with multiple transmitters. We present numerical results to demonstrate the effectiveness of the proposed scheme under a variet...

A Cognitive Radio (CR) network should be able to sense its environment to adapt its communication so that it can utilize unused licensed spectrum without interfering with incumbent users. Properly modeling the expected interference from the entire CR network is there- fore very important to effectively protect these incumbent users. We model the accumulative interference generated from a large-scale CR

Opportunistic spectrum access presents a new approach to wireless spectrum utilization and management. In this paper, we propose a non-cooperative based OSA approach: learning-based approach to allow multiple secondary users to achieve maximal throughput in an unslotted opportunistic spectrum access (OSA) network. In this approach, collisions among secondary users are taken into consideration while making channel sensing decisions. Spectrum maps for secondary users are estimated based on occurrence of collisions. Our approach allows secondary users to achieve maximal throughput by seeking independent spectrum opportunities without exchanging any control information among secondary users. Numerical results show that the learning-based approach obtains near-optimal performance in most of the scenarios.