The Theory of Matrices. By F R. Gantmacher. Two volumes, pp. 374 and 276. 1959. (Translated from the Russian by K. A. Hirsch; Chelsea Publishing Company, New York)

Cooperative spectrum sensing in cognitive radio networks: A survey

The ever-increasing demand for higher data rates in wireless communications in the face of limited or underutilized spectral resources has motivated the introduction of cognitive radio. Traditionally, licensed spectrum is allocated over relatively long time periods and is intended to be used only by licensees. Various measurements of spectrum utilization have shown substantial unused resources in frequency, time, and space [1], [2]. The concept behind cognitive radio is to exploit these underutilized spectral resources by reusing unused spectrum in an opportunistic manner [3], [4]. The phrase cognitive radio is usually attributed to Mitola [4], but the idea of using learning and sensing machines to probe the radio spectrum was envisioned several decades earlier (cf., [5]).

Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances

Adaptive networks are well-suited to perform decentralized information processing and optimization tasks and to model various types of self-organized and complex behavior encountered in nature. Adaptive networks consist of a collection of agents with processing and learning abilities. The agents are linked together through a connection topology, and they cooperate with each other through local interactions to solve distributed optimization, estimation, and inference problems in real-time. The continuous diffusion of information across the network enables agents to adapt their performance in relation to streaming data and network conditions; it also results in improved adaptation and learning performance relative to non-cooperative agents. This article provides an overview of diffusion strategies for adaptation and learning over networks, with emphasis on mean-square-error designs. Stability and performance analyses are provided and the benefits of cooperation are highlighted. Several supporting appendices are included in an effort to make the presentation self-contained for most readers.

Diffusion adaptation over networks

Cognitive radio (CR) can successfully deal with the growing demand and scarcity of the wireless spectrum. To exploit limited spectrum efficiently, CR technology allows unlicensed users to access licensed spectrum bands. Since licensed users have priorities to use the bands, the unlicensed users need to continuously monitor the licensed users' activities to avoid interference and collisions. How to obtain reliable results of the licensed users' activities is the main task for spectrum sensing. Based on the sensing results, the unlicensed users should adapt their transmit powers and access strategies to protect the licensed communications. The requirement naturally presents challenges to the implementation of CR. In this article, we provide an overview of recent research achievements of including spectrum sensing, sharing techniques and the applications of CR systems.

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Ten years of research in spectrum sensing and sharing in cognitive radio

Phase noise causes significant degradation in the performance of orthogonal frequency division multiplexing (OFDM)-based wireless communication systems. The presence of phase noise can reduce the effective signal-to-noise ratio (SNR) at the receiver, and consequently, limit the bit error rate (BER) and data rate. In this paper, the effect of phase noise on OFDM wireless systems is studied, and a compensation scheme is proposed to mitigate the common phase error and intercarrier interference (ICI) caused by phase noise. In the proposed scheme, the communication between the transmitter and receiver blocks consists of two stages. In the first stage, block-type pilot symbols are transmitted and the channel coefficients are jointly estimated with the phase noise in the time domain. In the second stage, comb-type OFDM symbols are transmitted such that the receiver can jointly estimate the data symbols and the phase noise. It is shown both by theory and computer simulations that the proposed scheme can effectively mitigate the ICI caused by phase noise and improve the BER of OFDM systems. Another benefit of the proposed scheme is that the sensitivity of OFDM receivers to phase noise can be significantly lowered, which helps simplify the oscillator and circuitry design in terms of implementation cost and power consumption.

Compensation of Phase Noise in OFDM Wireless Systems

Efficient and reliable spectrum sensing plays a critical role in cognitive radio networks. This paper presents a cooperative sequential detection scheme to reduce the average sensing time that is required to reach a detection decision. In the scheme, each cognitive radio computes the log-likelihood ratio for its every measurement, and the base station sequentially accumulates these log-likelihood statistics and determines whether to stop making measurement. The paper studies how to implement the scheme in a robust manner when the assumed signal models have unknown parameters, such as signal strength and noise variance. These ideas are illustrated through two examples in spectrum sensing. One assumes both the signal and noise are Gaussian distributed, while the other assumes the target signal is deterministic.

Cooperative Sensing via Sequential Detection

Physical impairments like IQ imbalance and phase noise can cause significant degradation in the performance of wireless communication systems. In this paper, the joint effects of IQ imbalance and phase noise on OFDM systems are analyzed, and a compensation scheme is proposed to improve the system performance in the presence of IQ imbalance and phase noise. The scheme consists of a joint estimation of channel and impairment parameters and a joint data symbol estimation algorithm. It is shown both by theory and computer simulations that the proposed scheme can effectively improve the signal-to-noise ratio at the receiver. As a result, the sensitivity of OFDM receivers to the physical impairments can be significantly lowered, simplifying the RF and analog circuitry design in terms of implementation cost, power consumption, and silicon fabrication yield.

Joint compensation of IQ imbalance and phase noise in OFDM wireless systems

The wideband RF receiver in a software-defined radio (SDR) system suffers from the nonlinear effects caused by the front-end analog processing. In the presence of strong blocker (interference) signals, such nonlinearities introduce severe cross modulation over the desired signals. This paper investigates how the cross-modulation distortion can be compensated for by using digital signal processing techniques. In the proposed solution, the SDR scans the wide spectrum and locates the desired signal and strong blocker signals. After down-converting these signals separately to the baseband, the baseband processor processes them jointly to mitigate the cross-modulation interferences. As a result, the sensitivity of the wideband RF receiver to the nonlinearity impairment can be significantly lowered, simplifying the RF and analog circuitry design in terms of implementation cost and power consumption. The proposed approach also demonstrates how mixed-signal, i.e., joint analog and digital, processing techniques play a critical role in the emerging SDR and cognitive radio technologies.

Digital Compensation of Cross-Modulation Distortion in Software-Defined Radios

A new approach to robust adaptive beamforming for wideband array signals is proposed. General steering vector errors, such as direction-of-arrival mismatch and array positional error, are modeled by "time-delay errors" and compensated for by self-adjusted interpolation filtering. The proposed method effectively overcomes the target-signal cancellation problem without suffering from loss in the degree of freedom for interference rejection, as verified by simulations.

Qiyue Zou

Papers

Compensation of Phase Noise in OFDM Wireless Systems

Cooperative Sensing via Sequential Detection

Joint compensation of IQ imbalance and phase noise in OFDM wireless systems

Digital Compensation of Cross-Modulation Distortion in Software-Defined Radios

A robust algorithm for linearly constrained adaptive beamforming