Spectrum-Efficient Wireless Sensor Networks

In the past decade, several short range wireless technologies, for example, IEEE 802.15.4, WirelessHART, and ISA 100, have been developed for wireless sensor networks (WSNs). These WSN related technologies primarily operate in the unlicensed ISM (industrial, scientific, and medical) band which is shared with other major wireless standards such as IEEE 802.11, Bluetooth, and cordless phone. With the growing proliferation of wireless devices and systems, the ISM band is increasingly becoming congested and the coexistence issues are becoming more and more critical for the applications of WSNs. The key is how to minimize the mutual interference and maximize the spectrum utilization. A promising solution is to exploit opportunistic spectrum access approaches via cognitive radios (CRs) to solve the spectrum congestion and interference issues. To this end, cognitive radio sensor network (CRSN) is proposed as a paradigm that aims to utilize cognitive radio techniques to traditional WSNs.

The objective of this special issue is to provide a chance for both academic and industry professionals to discuss recent progress in the area of spectrum-efficient wireless sensor networks involving cognitive radios and other new techniques. This special issue consists of the following papers selected from a much larger set of submissions after several rounds of review by the invited reviewers.

In the paper “Selective Sensing and Access Strategy to Maximize Throughput in Cognitive Radio Sensor Network,” the authors presented a selective spectrum sensing and access strategy in a CRSN to maximize the throughput of secondary user (SU) system. The SU only selects part (instead of all) of the channels for spectrum sensing and accesses these channels based on the sensing results. A selection-making algorithm based on partially observable Markov decision process (POMDP) theory was proposed to make the SU determine which channels are selected for sensing, how long the sensing time is, and the transmission powers of channels. An optimal policy and a myopic policy were proposed to solve the POMDP problem. Numerical results showed that the proposed selective spectrum sensing and access strategy improves the system performance efficiently.

In the paper “Cognitive Multihop Wireless Sensor Networks over Nakagami-m Fading Channels,” the authors studied the performance of a cluster-based cognitive multihop WSN with decode-and-forward (DF) partial relay selection over Nakagami-m fading channels. They derived the closed-form expressions for the exact outage probability and bit error rate (BER) of the secondary system. Asymptotic outage analysis reveals that the diversity order is determined by the minimum fading severity parameter of all the secondary transmission links, irrespective of the channel state information (CSI) imperfection. The fading severity of the secondary transmission links has more influence on the outage performance than that of the interference links. They also showed that increasing the number of relaying hops is an effective way to improve their transmission performance, and increasing the number of available relays in each cluster can mitigate the performance degradation caused by CSI imperfection.

In the paper “A Lightweight Classification Algorithm for External Sources of Interference in IEEE 802.15.4-Based Wireless Sensor Networks Operating at the 2.4 GHz,” a lightweight classification algorithm was presented to detect the common external sources of interference in the 2.4 GHz frequency band. The algorithm uses the energy detection (ED) feature of an IEEE 802.15.4-compliant radio and thus classifies the interferers without demodulation of their signals. The algorithm has no need to change the channel since it relies on time patterns instead of spectral features. The algorithm was extensively tested in a radio frequency anechoic chamber and in real world scenarios (e.g., IEEE 802.11b/g/n, Bluetooth, and microwave ovens).

In the paper “Maximizing Throughput with Wireless Spectrum Sensing Network Assisted Cognitive Radios,” a dedicated wireless spectrum sensing network (WSSN) was proposed to eliminate sensing time from SUs and thus improve achievable throughput. In addition, the sensing duration due to the dedicated WSSN is not limited to a small time interval, which decreases the probability of false alarm and achieves a targeted high probability of detection. A low probability of false alarm increases the spectrum utilization and improves the throughput, while a high detection probability protects the primary users. The authors finally provided simulation results to demonstrate the effectiveness of the proposed techniques.

In the paper “On the Optimality of Generic Rate-Based AIMD and AIAD Congestion Control Schemes in Cognitive Radio Sensor Networks,” the authors developed an analytical framework to study the optimality of rate-based generic AIMD and AIAD congestion control schemes for cognitive radio sensor networks (CRSNs). A congestion model was introduced to describe the congestion behavior of the CRSNs. A semi-Markov chain (SMC) was proposed to model the steady-state sending rate distribution of source nodes based on the congestion model. The optimality of generic AIMD and AIAD, based on the proposed models, was analyzed in order to maximize the defined rate-congestion ratio (RCR). The analytical results were verified through NS2-based simulations.