General analytical framework for cooperative sensing and access trade-off optimization

In this paper, we investigate the joint cooperative spectrum sensing and access design problem for multi-channel cognitive radio networks. A general heterogeneous setting is considered where the probabilities that different channels are available, SNRs of the signals received at secondary users (SUs) due to transmissions from primary users (PUs) for different users and channels can be different. We assume a cooperative sensing strategy with a general a-out-of-b aggregation rule and design a synchronized MAC protocol so that SUs can exploit available channels. We analyze the sensing performance and the throughput achieved by the joint sensing and access design. Based on this analysis, we develop algorithms to find optimal parameters for the sensing and access protocols and to determine channel assignment for SUs to maximize the system throughput. Finally, numerical results are presented to verify the effectiveness of our design and demonstrate the relative performance of our proposed algorithms and the optimal ones.Comment: arXiv admin note: text overlap with arXiv:1404.167

Multiband Spectrum Access: Great Promises for Future Cognitive Radio Networks

Cognitive radio has been widely considered as one of the prominent solutions to tackle the spectrum scarcity. While the majority of existing research has focused on single-band cognitive radio, multiband cognitive radio represents great promises towards implementing efficient cognitive networks compared to single-based networks. Multiband cognitive radio networks (MB-CRNs) are expected to significantly enhance the network's throughput and provide better channel maintenance by reducing handoff frequency. Nevertheless, the wideband front-end and the multiband spectrum access impose a number of challenges yet to overcome. This paper provides an in-depth analysis on the recent advancements in multiband spectrum sensing techniques, their limitations, and possible future directions to improve them. We study cooperative communications for MB-CRNs to tackle a fundamental limit on diversity and sampling. We also investigate several limits and tradeoffs of various design parameters for MB-CRNs. In addition, we explore the key MB-CRNs performance metrics that differ from the conventional metrics used for single-band based networks.Comment: 22 pages, 13 figures; published in the Proceedings of the IEEE Journal, Special Issue on Future Radio Spectrum Access, March 201

Joint Cooperative Spectrum Sensing and MAC Protocol Design for Multi-channel Cognitive Radio Networks

In this paper, we propose a semi-distributed cooperative spectrum sen sing (SDCSS) and channel access framework for multi-channel cognitive radio networks (CRNs). In particular, we c onsider a SDCSS scheme where secondary users (SUs) perform sensing and exchange sensing outcomes with ea ch other to locate spectrum holes. In addition, we devise the p -persistent CSMA-based cognitive MAC protocol integrating the SDCSS to enable efficient spectrum sharing among SUs. We then perform throughput analysis and develop an algorithm to determine the spectrum sensing and access parameters to maximize the throughput for a given allocation of channel sensing sets. Moreover, we consider the spectrum sensing set optimization problem for SUs to maxim ize the overall system throughput. We present both exhaustive search and low-complexity greedy algorithms to determine the sensing sets for SUs and analyze their complexity. We also show how our design and analysis can be extended to consider reporting errors. Finally, extensive numerical results are presented to demonstrate the sig nificant performance gain of our optimized design framework with respect to non-optimized designs as well as the imp acts of different protocol parameters on the throughput performance.Comment: accepted for publication EURASIP Journal on Wireless Communications and Networking, 201

On achieving network throughput demand in cognitive radio-based home area networks

The growing number of wireless devices for in-house use is causing a more intense use of the spectrum to satisfy the required quality-of-service such as throughput. This has contributed to spectrum scarcity and interference problems particularly in home area networks (HAN). Cognitive radio (CR) has been recognized as one of the most important technologies which could solve these problems and sustainably meeting the required communication demands by intelligently exploiting temporarily unused spectrum, including licensed spectrum. In this paper, we propose a throughput demand-based cognitive radio solution for home area networks (TD-CRHAN) which aims at effectively and efficiently meet the ever-increasing throughput demand in HAN communication. It is shown numerically and by simulations that a TD-CRHAN can satisfy the requested throughput from the network devices and has high utilization of the available throughput. The analysis further shows that, by setting the achievable throughput to be as close as possible to the total demanded throughput (instead of maximizing it), a TD-CRHAN is able to relax the tight cooperative spectrum sensing requirements which significantly improves cooperative spectrum sensing parameters, such as the local spectrum sensing time and the number of cooperative spectrum sensing devices. Finally, it is shown that these cooperative spectrum sensing parameters can be further improved when additional channels are available

Smart Sensing and Performance Analysis for Cognitive Radio Networks

Static spectrum access policy has resulted in spectrum scarcity as well as low spectrum utility in today\u27s wireless communications. To utilize the limited spectrum more efficiently, cognitive radio networks have been considered a promising paradigm for future network. Due to the unique features of cognitive radio technology, cognitive radio networks not only raise new challenges, but also bring several fundamental problems back to the focus of researchers. So far, a number of problems in cognitive radio networks have remained unsolved over the past decade. The work presented in this dissertation attempts to fill some of the gaps in the research area of cognitive radio networks. It focuses primarily on spectrum sensing and performance analysis in two architectures: a single cognitive radio network and multiple co-existing cognitive radio networks. Firstly, a single cognitive radio network with one primary user is considered. A weighted cooperative spectrum sensing framework is designed, to increase the spectrum sensing accuracy. After studying the architecture of a single cognitive radio network, attention is shifted to co-existing multiple cognitive radio networks. The weakness of the conventional two-state sensing model is pointed out in this architecture. To solve the problem, a smart sensing model which consists of three states is designed. Accordingly, a method for a two-stage detection procedure is developed to accurately detect each state of the three. In the first stage, energy detection is employed to identify whether a channel is idle or occupied. If the channel is occupied, received signal is further analyzed at the second stage to determine whether the signal originates from a primary user or an secondary user. For the second stage, a statistical model is developed, which is used for distance estimation. The false alarm and miss detection probabilities for the spectrum sensing technology are theoretically analyzed. Then, how to use smart sensing, coupled with a designed media access control protocol, to achieve fairness among multiple CRNs is thoroughly investigated. The media access control protocol fully takes the PU activity into account. Afterwards, the significant performance metrics including throughput and fairness are carefully studied. In terms of fairness, the fairness dynamics from a micro-level to macro-level is evaluated among secondary users from multiple cognitive radio networks. The fundamental distinctions between the two-state model and the three-state sensing model are also addressed. Lastly, the delay performance of a cognitive radio network supporting heterogeneous traffic is examined. Various delay requirements over the packets from secondary users are fully considered. Specifically, the packets from secondary users are classified into either delay-sensitive packets or delay-insensitive packets. Moreover, a novel relative priority strategy is designed between these two types of traffic by proposing a transmission window strategy. The delay performance of both a single-primary user scenario and a multiple-primary user scenario is thoroughly investigated by employing queueing theory