Abstract Cognitive radio (CR) is a newly developed technology for increasing spectral efficiency in wireless communication systems. In the CR networks, there exist two traditional spectrum‐sharing technologies called spectrum overlay and spectrum underlay. A new hybrid overlay/underlay paradigm has also been discussed in the literature. In this work, we create a unified spectrum sensing and throughput analysis model, which is suitable for overlay, underlay, and hybrid overlay/underlay paradigms in the CR networks. In the proposed model, the energy detection scheme is employed for the spectrum sensing in the network in which the co‐channel interference is present among primary users and secondary users (SUs). The SUs' throughput in the proposed CR system model is then analyzed. The simulations are also carried out for demonstrating the performance of overlay, underlay, and hybrid overlay/underlay paradigms. Copyright © 2013 John Wiley & Sons, Ltd.

This work proposes a distributed sampling design for the signal detection application in the cluster-based wireless sensor networks (WSNs). Considering the energy saving requirement in the cluster-based WSNs, a linear weighting data fusion scheme for data reduction at the cluster head is also developed in this paper. Both the distributed sampling and the data reduction schemes are designed based on Ali-Silvey distance measures. The objective functions are derived in a closed form and two numerical examples are presented to illustrate our distributed sampling design and data reduction scheme. Numerical results show that our sampling design outperforms the uniform sampling and is insensitive to the sampling jitter. The results also show that the performance loss caused by the data reduction is quiet small. Therefore, the proposed schemes are very suitable for the detection applications in battery-powered WSNs.

A novel methodology is proposed in this paper to design and implement an improved Digital Audio Broadcasting (DAB) channel codec that is based on Eureka-147 specifications including energy-dispersal, interleaving, concatenated Reed-Solomon and punctured convolutional coding techniques. Furthermore, by utilizing MATLAB/Simullink software, Xilinx System Generator, Xilinx Alliance tools, Xilinx XSE & ISE and Modelsim XE software, a transceiver platform is built-up to simulate and analyze the performance of the DAB channel codec based on FPGA hardware implementation. Rapid measurement of critical design considerations can be performed that include noise interference, multi-path fading, etc. Further, the proposed hardware platform can be used directly in practical DAB transmission.

In this paper, we present a sampling design for the weak signal detection in additive non-Gaussian noise. We employ the theory of spherically invariant random processes (SIRP) to express the non-Gaussian noise. Our approach for the design of sampling schemes is based on the class of Ali-Silvey distance measures. A design objective function for this problem is derived and is maximized to obtain the sampling scheme for the detection problem under consideration. Its detection performance is compared with that of the uniform sampling scheme by means of a numerical example. Comparisons show that our sampling design results in a superior performance.

This paper considers a system in which observations at a remote sensor are sampled and quantized, and then transmitted to a processor for signal detection. A constraint on the transmission rate is assumed. The problem of bit allocation among different samples is studied and illustrated by means of an example.