The authors propose Markovian‐based spectrum sensing policies in a cognitive radio system that leverages past sensing outcomes of several cooperating secondary users (SUs) to decide which channel (of primary users – PUs) should be sensed by each SU at a given time. These policies are based on a new finite‐state channel model that captures the fading condition as well as the occupancy state for each primary channel. The multiuser extension of this model is useful when multiple spatially distributed SUs share their sensing outcomes. The proposed schemes allow the asynchronous sensing outcomes obtained by the SUs over different slots to be fused together and converted into a posteriori probabilities for the current states of the primary channels. As the detection threshold in a spectrum detector balances the trade‐off between the false‐alarm and miss probabilities for detecting primary signals in a single primary channel, a design parameter is introduced to allow the system designer to devise policies with different levels of aggressiveness. The authors evaluate the optimality and complexity of the proposed sensing policies and show that our schemes significantly increase secondary use of the spectrum and/or reduce interference with PUs compared to a random selection policy or a cooperative sensing policy based on a two‐state channel model.

Recent findings in neuroscience have shown that the spectral components of electroencephalogram (EEG) signals convey information regarding the mental task not only in their power but also in their phase. This calls for the utilization of complex-valued spectrum, instead of the commonly used power spectral density, in designing the brain computer interfaces. This paper studies the complex-valued spectrum of the EEG signal recorded during mental imagery tasks, and provides a statistical model for the EEG spectral components. Motivated by the results of a recent work by the authors, this paper proposes a time-varying noncircularly-symmetric Gaussian model for complex-valued EEG spectrum during a mental imagery trial. It will be shown that the mean of this Gaussian model is constant over time, whereas its variance and pseudo-variance follow an autoregressive conditional heteroscedastic (ARCH) model. The validity of this model is then verified using statistical tests.

Classification of high-dimensional data typically requires extraction of discriminant features. This paper proposes a linear feature extractor, called whitened linear sufficient statistic (WLSS), which is based on the sufficiency conditions for heteroscedastic Gaussian distributions. WLSS approximates, in the least squares sense, an operator providing a sufficient statistic. The proposed method retains covariance discriminance in heteroscedastic data, while it reduces to the commonly used linear discriminant analysis (LDA) in the homoscedastic case. Compared to similar heteroscedastic methods, WLSS imposes a low computational complexity, and is highly generalizable as confirmed by its consistent competence over various data sets.

Due to the unique characteristics of sensor devices, finding the energy-efficient modulation with a low-complexity implementation (refereed to as green modulation) poses significant challenges in the physical layer design of Wireless Sensor Networks (WSNs). Toward this goal, we present an in-depth analysis on the energy efficiency of various modulation schemes using realistic models in the IEEE 802.15.4 standard to find the optimum distance-based scheme in a WSN over Rayleigh and Rician fading channels with path-loss. We describe a proactive system model according to a flexible duty-cycling mechanism utilized in practical sensor apparatus. The present analysis includes the effect of the channel bandwidth and the active mode duration on the energy consumption of popular modulation designs. Path-loss exponent and DC-DC converter efficiency are also taken into consideration. In considering the energy efficiency and complexity, it is demonstrated that among various sinusoidal carrier-based modulations, the optimized Non-Coherent M-ary Frequency Shift Keying (NC-MFSK) is the most energy-efficient scheme in sparse WSNs for each value of the path-loss exponent, where the optimization is performed over the modulation parameters. In addition, we show that the On-Off Keying (OOK) displays a significant energy saving as compared to the optimized NC-MFSK in dense WSNs with small values of path-loss exponent.

Adaptive Demodulation (ADM) is a new rate-adaptive system that operates without requiring Channel State Information (CSI) at the transmitter, instead using adaptive decision region boundaries at the receiver and encoding the data with a rateless code. This paper addresses the design and performance of an ADM scheme for two common differentially coherent schemes: M-DPSK and M-DAPSK. The optimal method for determining the most reliable bits for a given differential detection scheme is presented. In addition, simple (near-optimal) implementations are provided for recovering the most reliable bits from a received pair of differentially encoded symbols for systems using 16-DPSK and 16-DAPSK. The new receivers offer the advantages of a rate-adaptive system, without requiring CSI at the transmitter or a coherent phase reference at the receiver. Bit error analysis for the ADM system in both cases is presented along with numerical results of the spectral efficiency for the rate-adaptive systems operating over a Rayleigh fading channel.

We consider a scenario where multiple collaborating cognitive radios (CR's) try to jointly detect spectrum opportunities in a wide-band spectrum within a predefined spectrum sensing time T S . Each CR is equipped with a tunable bandpass filter (BPF) and is able to sense one frequency band (channel) at a time. The sensing time consists of L sensing slots of length T. During each sensing slot, each of the collaborating CR's is assigned to sense one of the primary channels and report its observation to the other CR's. The goal is to maximize the expected number of identified idle channels by optimally choosing the channels to be sensed by each of the collaborating CR's at each sensing slot. We derive closed-form solutions for an optimal spectrum sensing policy and the associated reward function for the case of two collaborating CR's where individual sensing decisions are fused together according to the OR-rule. We show that the gain due to the optimal sensing policy is more significant when the spectrum utilization is high.

This paper presents an in-depth analysis on the energy efficiency of Luby transform (LT) codes with frequency shift keying (FSK) modulation in a wireless sensor network (WSN) over Rayleigh fading channels with path-loss. We describe a proactive system model according to a flexible duty-cycling mechanism utilized in practical sensor apparatus. The present analysis is based on realistic parameters including the effect of channel bandwidth used in the IEEE 802.15.4 standard, active mode duration, and computation energy. A comprehensive analysis, supported by some simulation studies on the probability mass function of the LT code rate and coding gain, shows that among uncoded FSK and various classical channel coding schemes, the optimized LT coded FSK is the most energy-efficient scheme for distance d greater than the predetermined threshold level dT, where the optimization is performed over coding and modulation parameters. In addition, although the optimized uncoded FSK outperforms coded schemes for d <; dT , the energy gap between LT coded and uncoded FSK is negligible for d <; dT compared to the other coded schemes. These results come from the flexibility of the LT code to adjust its rate to suit instantaneous channel conditions and suggest that LT codes are beneficial in practical low-power WSNs with dynamic position sensor nodes.

The use of wireless implant technology requires correct delivery of the vital physiological signs of the patient along with the energy management in power-constrained devices. Toward these goals, we present an augmentation protocol for the physical layer of the medical implant communications service (MICS) with focus on the energy efficiency of deployed devices over the MICS frequency band. The present protocol uses the rateless code with the frequency-shift keying (FSK) modulation scheme to overcome the reliability and power cost concerns in tiny implantable sensors due to the considerable attenuation of propagated signals across the human body. In addition, the protocol allows a fast start-up time for the transceiver circuitry. The main advantage of using rateless codes is to provide an inherent adaptive duty cycling for power management, due to the flexibility of the rateless code rate. Analytical results demonstrate that an 80% energy saving is achievable with the proposed protocol when compared to the IEEE 802.15.4 physical layer standard with the same structure used for wireless sensor networks. Numerical results show that the optimized rateless coded FSK is more energy efficient than that of the uncoded FSK scheme for deep tissue (e.g., digestive endoscopy) applications, where the optimization is performed over modulation and coding parameters.

Our goal is to present an overview of a class of low complexity detectors working in linear fading multipath channels. In addition, we present briefly a unified theory based on the optimal maximum a posteriori probability (MAP) receiver concept (Woodward & Davies, 1952), which in additive Gaussian noise leads to the estimator-correlator receiver (Price, 1956; Middleton, 1957; Kailath, 1960; Kailath, 1969). The terms receiver and detector are interchangeable. Detectors are estimators where the parameter or symbol set to be estimated is discrete (Kay, 1993; Kay, 1998). We consider phase-unaware detectors (PUDs) such as differentially coherent detector (DD), noncoherent detector (ND), and energy detector (ED). The term PUD is used to emphasize that the receiver does not have any knowledge of the absolute phase of the received signal although it may have some knowledge of the internal phase structure. We use the term noncoherent to represent a special case of PUD system, and this will be clarified later. PUD detectors are more robust than coherent detectors in a fading multipath channel since the carrier phase of a signal with a wide bandwidth or high carrier frequency may be difficult to estimate with a low complexity. Earlier extensive reviews include (Schwarz et al., 1966; Van Trees, 1971) and more recently (Garth & Poor, 1994; McDonough & Whalen, 1995; Proakis, 2001; Mammela et al., 2002; Simon & Alouini, 2005; Witrisal et al., 2009). A summary of the estimator-correlator receiver is presented in (Kay, 1998). Unless stated otherwise, we exclude equalizers which increase the complexity of the receiver significantly (Lodge & Moher, 1990; Colavolpe & Raheli, 1999). Thus we avoid intersymbol interference (ISI) by signal design and concentrate on the reception of a single symbol, which may include several bits in 警-ary communications. It is, however, conceptually straightforward to generalize the single symbol or “one-shot”detectors to symbol sequence detection by replacing the symbols by symbol sequences. The noise is assumed to be additive white Gaussian noise (AWGN). The frequency offset caused by the channel is assumed to be known and compensated. We also assume that the receiver is synchronous in the sense that the start of each symbol interval is known. Estimation of frequency and timing is a highly nonlinear problem, which is studied in (Mengali & D’Andrea, 1997; Meyr et al., 1998), see also (Turin, 1980). Also because of complexity reasons in general we exclude coherent detectors which are such that they assume that the alternative received

The use of wireless body area networks requires correct delivery of the vital signs of the patient while managing precious energy in tiny biosensors. Toward these goals, we present an energy-efficient protocol suitable for the narrow band physical layer of the IEEE 802.15.6 standard in on-body sensor networks. This study considers a realistic channel model inspired by the Gilbert-Elliott channel including the erasure mode and a binary symmetric channel model. This work studies the feasibility of Raptor codes, the most efficient rateless codes, with the Frequency Shift Keying (FSK) modulation to overcome the reliability and power cost concerns in on-body sensor devices. The main advantage of using Raptor codes is to provide an inherent adaptive power management, due to the flexibility of the code rate and coding gain. Numerical results show that the Raptor coded FSK is more energy efficient and robust than that of the uncoded FSK and LDPC codes, in various channel realization, in particular, when patients make sequential position changes.

Cognitive radios try to exploit “blank spaces” in the licensed band which are not being used by primary users at a particular place and time. In the absence of cooperation between the primary and the secondary networks, spectrum sensing enables secondary users to monitor a licensed band in order to find idle channels for opportunistic access. In this work, we propose a two-stage spectrum detection strategy that decreases the average channel search time by allowing the spectrum detector to focus on frequency channels which are more likely to be vacant. We show that the proposed detection strategy significantly outperforms the conventional single-stage strategy when the spectrum utilization is high.

This paper proposes a new receiver structure for linear-dispersion (LD) codes, subsuming orthogonal, quasiorthogonal and V-BLAST codes. We suggest to use widely-linear minimum-mean-squared-error (WL-MMSE) estimates of transmitted symbols in lieu of the sufficient statistics for maximum likelihood (ML) detection of these symbols. Proposed structure offers both optimal (ML) and suboptimal solutions. Simulation results show that the suboptimal receiver performs close to the optimal one, while reducing the receiver's complexity. Structure of the proposed receiver is particularly studied for orthogonal and quasi-orthogonal LD codes. Specifically, it is proved that Alamouti's combining scheme provides WL-MMSE estimates of the transmitted symbols.

Due to unique characteristics of sensor nodes, choosing an energy-efficient modulation scheme with low-complexity implementation (refereed to as green modulation) is a critical factor in the physical layer of Wireless Sensor Networks (WSNs). The main goal of this paper is to analyze and compare the energy efficiency of various sinusoidal carrier-based modulation schemes using parameters in the IEEE 802.15.4 standard and state-of-the art technology to find the best scheme in a dense WSN over frequency-flat Rayleigh fading channel with path-loss. Experimental results show that M-ary Frequency Shift Keying (MFSK) with small order of M has significant energy saving compared to OQPSK and MQAM for short range scenarios, and could be considered as a realistic candidate in dense WSNs. In addition, MFSK has the advantage of less complexity and cost in implementation than the other schemes.

In this letter, a design metric of the interleaver is derived from the union bound of the bit error rate (BER) of linearly precoded orthogonal frequency division multiplexing (OFDM) systems, assuming that the power-delay profile of the channel is known at the transmitter. A new cyclic shift interleaving scheme is proposed to improve the BER performance of OFDM systems. The proposed interleaving scheme is parameterized, and it incorporates existing interleaving schemes. The simulation results indicate that the proposed interleavers outperform the existing interleavers by up to 1.5 dB in a practical scenario.

This paper develops a family of irregular convolutional codes for bit-interleaved coded modulation (BICM) systems under iterative detection and decoding. Irregular convolutional codes are constructed through irregular puncturing over multiple mother codes of different memory. Strategies based on fixed- and variable-size trellises are proposed to connect different memory mother codes. The use of irregular puncturing and code memory yields improved coding efficiency with the aid of extrinsic information transfer charts. Under ergodic and quasi-static fading conditions, multiantenna BICM systems using the proposed codes outperform comparable turbo-coded systems and multilevel coding strategies.

The problem of iterative detection/decoding of data symbols transmitted over an additive white Gaussian noise (AWGN) channel in the presence of phase uncertainty is addressed in this paper. By modelling the phase uncertainty either as an unknown deterministic variable/process or random variable/process with a known a priori probability density function, a number of non-Bayesian and Bayesian detection algorithms with various amount of suboptimality have been proposed in the literature to solve the problem. In this paper, a new set of suboptimal iterative detection algorithms is obtained by utilizing the variational bounding technique. Especially, applying the generic variational Bayesian (VB) framework, efficient iterative joint estimation and detection/decoding schemes are derived for the constant phase model as well as for the dynamic phase model. In addition, the relation of the VB-based approach to the optimal noncoherent receiver as well as to the classical approach via the expectation-maximization (EM) algorithm is provided. Performance of the proposed detectors in the presence of a strong dynamic phase noise is compared to the performance of the existing detectors. Furthermore, an incremental scheduling of the VB (or EM) algorithm is shown to reduce the overall complexity of the receiver.

In this paper, we propose a duality-optimization based framework to maximize the weighted sum throughput for a multiple-input multiple-output (MIMO) ad hoc network. The new schemes include an approximate global optimization approach and an iterative search approach based on the duality framework. Transmitter adaptive precoding and receiver minimum mean-square-error (MMSE) detection for interference suppression are considered. Simulation results show that a significantly higher throughput is achieved for the dual optimization schemes than for the fixed mode precoding schemes and the transmit iterative waterfilling (IWF) scheme. The negative effects of transmit and receive antenna correlations are also studied. Results show that the proposed schemes are more robust against both transmit and receive correlations than the fixed-mode and IWF schemes.

In a wide range of communication systems, including DS-CDMA and OFDM systems, the signal-of-interest might be corrupted by an improper (F.D. Neeser et al.,1993) (also called non circularly symmetric (B. Picinbono, 1994)) interfering signal. This paper studies the maximum likelihood (ML) detection of binary signals in the presence of additive improper complex Gaussian noise. Proposing a new measure for noncircularity of complex random variables, we will derive the ML decision rule and its performance based on this measure. It will be shown that the ML detector performs pseudo correlation (F.D. Neeser et al.,1993) as well as conventional correlation of the observation to the signals-of-interest. As an alternative solution, we will propose a filter for converting improper signals to proper ones, called circularization filter, and will utilize it together with a conventional matched-filter (MF) to construct an ML detector.

This paper presents a novel precoder design for an orthogonal frequency division multiplexing (OFDM) system using a channel estimator. First, an asymptotically tight approximation of the pairwise error probability (PEP) error with channel estimation error is presented and is shown to improve the existing upper bound of the PEP. Using the proposed approximation, a near-optimal power allocation scheme is derived and investigated and a new precoding scheme is introduced to improve the bit error rate (BER) performance of the receiver assisted by a minimum mean square error (MMSE) channel estimator. Both experimental and theoretical results included in this paper show improvement in the BER performance of a receiver with channel estimators utilizing the introduced precoder and power allocation scheme.

In this paper, we derive general asymptotic moment generating function (MGF) expressions of the GSC output signal- to-noise ratio (SNR) for generalized correlated fading channels assuming large average signal-to-noise ratio (ASNR). Based on the MGF result, the asymptotic diversity and combining gains for correlated-diversity GSC are derived. Our analytical results reveal that over correlated channels when the channel covariance matrix is full rank the diversity gain of GSC is to equivalent to that of maximum ratio combining (MRC) with independent fading branches. The combining gains for different modulation formats and fading types in correlated channels are also derived. As is known and analytically verified in this paper, for channels without line-of-sight (LoS) components, correlation generally degrades the GSC combining gain. However, we show that for Rician channels the LoS phase vector affects the performance, and near-optimal LoS phase vector brings a larger combining gain than even the independent fading channels.