Benjian Hao

On the Performance of Cognitive Relay Networks Under Primary User's Outage Constraint

In this letter, we propose two relay selection schemes in cognitive relay networks. According to the proposed schemes, the number of relays involved in the opportunistic relaying is determined by the partial channel state information (CSI) of primary user link and partial CSI between the relays and the primary user receiver, so as to maintain the primary users outage probability below a predetermined value. The exact outage probabilities of the secondary user are derived over Rayleigh fading channels. Finally, simulation results validate our analysis.

Performance Analysis of Adaptive Modulation in Cognitive Relay Network With Cooperative Spectrum Sensing

In practice, sensing results often affect the data transmission in cognitive radio systems. Therefore, a hybrid interweave/underlay cognitive radio system is presented by jointly considering spectrum sensing and data transmission. In particular, multiple relays are deployed for both the spectrum sensing and data transmission. The secondary user (SU) source and the relays cooperatively sense the spectrum with energy detection and decision fusion. According to the cooperative spectrum sensing results, the SU adaptively switches between interweave and underlay spectrum access mode. Moreover, to improve the spectral efficiency, an adaptive modulation technique is integrated into SUs transmission. In this context, undertaking the interference from the primary user (PU), the upper bound for average spectral efficiency of the SU with continuous-rate adaptive modulation is derived over Rayleigh fading channels. Further, we study the performance of SU, where adaptive L-ary quadrature amplitude modulation (L-QAM) with fixed switching threshold is adopted. Simulation results verify our analysis and show that both hybrid interweave/underlay scheme and adaptive modulation can improve the SUs performance significantly.

Passive multiple disjoint sources localization using TDOAs and GROAs in the presence of sensor location uncertainties

Passive source localization has been the focus of considerable research efforts due to its usefulness in various applications. This paper performs a fundamental investigation of whether the gain ratios of arrival (GROAs) can be utilized in conjunction with the time differences of arrival (TDOAs) to improve the multiple sources localization accuracy with erroneous sensor positions. Its an urgent need to find a closed-form solution with good localization accuracy for this challenging problem. This paper takes the advantage that the TDOAs and GROAs from different sources have the same sensor position displacements and proposes an estimator that jointly estimates the unknown sources and sensor positions. In order to establish an closed-form solution for multiple sources location estimates using GROAs and TDOAs, we use the idea of hypothesized source locations in the algorithm development to enable the formulation of pseudo-linear equations. The proposed algebraic solution does not require initialization and does not have divergence problem. Our conclusion is that the improvement from GROAs is obvious for multiple sources localization compared with methods only using TDOAs. Numerical simulations are included to support and corroborate the theoretical developments.

On the Cramer-Rao bound of multiple sources localization using RDOAs and GROAs in the presence of sensor location uncertainties

Passive source localization has been the focus of considerable research efforts due to its usefulness in various applications. This paper performs a fundamental investigation of whether the gain ratios of arrival (GROAs) can be utilized in conjunction with the range differences of arrival (RDOAs) to improve the multiple sources localization accuracy in the presence of sensor location uncertainties. In this paper, we derive the Cramer-Rao lower bound (CRLB) of multiple source location estimate using both RDOAs and GROAs when sensor positions have errors. Simulations show that the localization accuracy improvements contributed by GROA measurements are significant for two far-field sources, two near-field sources and two enclosed sources as the SNR, jamming signal bandwidth factor C/ωo or sensor position error power σs2 increases. The CRLB will provide reasonable reference for localization algorithm research in the future.

An adaptive receiver of joint data and channel estimation for meteor burst communications

In view of the characteristics of the meteor burst channel, the variable rate data transmission should be adopted to improve the system average throughput, which results in channel tracing and equalization problems at the receiver. Although the joint data and channel estimation of maximum likelihood sequence detection performing the principle of per-survivor processing (PSP) is considered as an optimal detection scheme, its great computational complexity is a major problem and can hardly agree with the decreasing of the meteor channel. Based on the estimation of the system parameters, an adaptive state reduction of the PSP (ASRP) algorithm with only a few states in the trellis diagram is employed, while these states are chosen by the time-varying threshold according to the exponential decay of meteor channels. It is shown that, ASRP can make a good tradeoff between the performance and the computational complexity, and provides reliable data transmission for adaptive modulation and coding of the meteor burst communication system. Computer simulation results and performance analysis are also included to support our developments. Copyright

Maximum-Eigenvalue-Based Sensing and Power Recognition for Multiantenna Cognitive Radio System

Spectrum sensing, as a way for a secondary user (SU) to detect the on/off status of the primary user (PU), has been well studied in the area of cognitive radio (CR) for the past ten years. It is noticed that most exiting techniques only assumed that the PU has constant transmit power, although in practice, the PU could possibly operate under more than one discrete power levels, as can be seen from many practical standards, e.g., 802.11, Global System for Mobile Communications, and Long-Term Evolution. In this paper, we investigate this new multiple primary transmit power (MPTP) scenario and propose the corresponding detection/recognition framework based on multiple-antenna configuration at the SU. Although the primary target in MPTP is still to detect the on/off status of the PU, a secondary target appears in order to identify PUs transmit power level once the PU is “detected” in the first place. To achieve these two targets, an eigenvalue-based approach is applied due to its robustness and least requirement on the knowledge of channels. To obtain the closed-form threshold expressions and the performance analysis, we adopt nonasymptotic Gaussian and Gamma approximation for the distribution of the eigenvalues of the sample covariance matrix. Simulation results are provided to verify the proposed studies.

Time delay estimation of co-frequency signals in TDOA localization based on WSN

The time delay estimation of the TDOA is signification in passive source localization systems, and the estimation accuracy may directly affect the source location performance. We address the problem of passive blind estimation of time-delay for uncorrelated co-frequency interference source signal based on wireless sensor network (WSN). The received mixtures are modeled as unknown linear combinations of differently delayed versions of communication signal and interference signal. Two methods of Blind Source Separation (BSS) and Secondary Interference Signal Extracting (SISE) are introduced in the proposed method. The interference signals in the mixed receiving signals of all sensors are extracted effectively and the affection of the mixed communication signals can be significantly reduced. Simulations results demonstrate that the proposed method has a more accurate performance compared to some other time delay estimation methods.

Analysis of asynchronous frequency hopping multiple-access network performance based on the frequency hopping sequences

In this study, the authors investigate the impact of the frequency-hopping (FH) sequence on the packet transmission performance of the asynchronous frequency-hopping multiple-access (FHMA) network. According to the model of the asynchronous FHMA network given in this study, the authors analyse the impact of the two important FH sequence factors – uniformity and frequency slot number – on the correct transmission probability and the packet transmission frequency efficiency. According to the non-collision probability analysed in this study, the uniformity of the FH sequence is an important issue to determine the correct packet transmission probability. Moreover, based on the definition of the packet transmission frequency efficiency given in this study, the optimal frequency slot number employed to obtain the maximum frequency efficiency is obtained. By employing three typical FH sequences, the simulation results are also included, which validates the theoretical analysis about the packet transmission performance of the asynchronous FHMA network.

Joint source localisation and sensor refinement using time differences of arrival and frequency differences of arrival

The accuracy of sources locations and velocities estimate is very sensitive to the accurate knowledge of sensor locations and velocities. In the presence of sensor position and velocity errors, this study considers the problem of simultaneously locating multiple disjoint sources and refining erroneous sensor positions and velocities using time differences of arrival and frequency differences of arrival. The previous work by Sun and Ho to solve this problem provided an efficient estimator for multiple disjoint sources, but it cannot provide optimum accuracy for the sensor positions and sensor velocities. In many practical applications, it is necessary and helpful to refine sensor locations and velocities while localising multiple sources. The proposed method improves the previous method so that both the source and the sensor position and velocity estimates can achieve the Cramer-Rao lower bound accuracy very well over small noise region. The theoretical derivation is corroborated by simulations.

A Self-Adapting Symbol Rate Estimator Based on Wavelet Transform with Optimal Scale and Resample

Traditional symbol rate estimators based on wavelet transform (WT) suffer from difficulties in choosing wavelet scale. Additionally, the most estimators are only adapted to limited signal types. Furthermore, those estimators are susceptible to noise, which is impractical to implement. In this paper, to overcome shortages of those traditional estimators, a self- adapting symbol rate estimator is proposed. The proposed estimator has advantages in reliably working under low Eb-to-N0. More importantly, it can be widely used to estimate various types of signal. The numerical simulations show that the proposed estimator has superiority in performance compared with the improved estimators based on wavelet transform.