Low-complexity fractional phase estimation for totally blind channel estimation

To remove the scalar ambiguity in conventional blind channel estimation algorithms, totally blind channel estimation （TBCE） is proposed by using multiple constellations. To estimate the unknown scalar, its phase is decomposed into a fractional phase and an integer phase. However, the maximum-likelihood （ML） algorithm for the fractional phase does not have closed-form solutions and suffers from high computational complexity. By ex- ploring the structures of widely used constellations, this paper proposes a low-complexity fractional phase estimation algorithm which requires no exhaustive search. Analytical expressions of the asymptotic mean squared error （MSE） are also derived. The theo- retical analysis and simulation results indicate that the proposed fractional phase estimation algorithm exhibits almost the same performance as the ML algorithm but with significantly reduced computational burden.

Blind channel estimation for redundant precoded OFDM systems

Considering that channel estimation can play a crucial role in coherent detection of the information symbols in each data block, a blind channel estimation approach is proposed for redundant precoded orthogonal frequency-division multiplexing （OFDM） systems. A redundant linear frequency-domain precoder is applied to each pair of blocks before they enter the OFDM system. Because of the introduced structure, the frequency-selective channel can be identified at the receiver based on autocorrelation operations, singular value decomposition （SVD）, and by resolving the scalar ambiguity. The proposed channel estimation method has low computational complexity and requires no prior statistical information on channel or noise. And the proposed blind method has high spectral efficiency owing to exploiting no training sequence. Computer simulations confirm that this proposed blind channel estimation method can identify the frequency-selective channels perfectly and obtain a good performance.

Subspace-Based Blind Channel Estimation Method for MIMO-OFDM Systems

A subspace-based blind channel estination algo rithm for MIMO-OFDM systems is proposed. This algorithm exploits the cyclostationarity introduced by cyclic prefix of OFDM to estimate the channel parameters. The proposed new algorithm is found to be outperforming the other algorithm with respect to convergence rate and achievable mean square error and robustness to channel order over determination.

Equivalent Time-Domain Representation and Uplink Channel Estimator for Multicarrier CDMA Systems

Many blind channel estimation methods have been proposed for direct sequence (DS) code-division multiple access (CDMA) systems, so we can certainly use them to estimate the finite impulse response (FIR) channel for the multi-carrier (MC-) CDMA system. In this paper, the MC-CDMA system is interpreted as an equivalent time-domain DS-CD-MA system with specific spreading codes. Then, an equivalently time-domain blind channel estimator is derived for the uplink MC-CDMA, which is based on second-order statistics of the received data. By exploiting singular value decomposition (SVD) and the finite alphabet property of transmitted symbols, the time-domain channel impulse response (CIR) for the uplink MC-CDMA can be accurately identified. Computer simulations illustrate both the validity and the overall performance of the proposed estimator.

Estimating Digital Inter-Symbol Interference Channel Blindly Based on the One-Step Branch Transition Rules in Trellises

A novel discrete-time digital inter-symbol interference (ISI) channel blind estimation sub-optimal algorithm is proposed. This algorithm reduces the complexity of the optimal maximum likelihood sequence estimation (MLSE) considerably based on the one-step branch transition rules in trellises, and is suitable for the estimation of the channels with small lengths of ISI.

On detecting primary user emulation attack using channel impulse response in the cognitive radio network

Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service(DoS) attack,named the ‘primary user emulation attack(PUEA)', exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response(CIR) between the secondary user(SU) and the signal source is used to determine whether the received signal is transmitted by the primary user(PU) or the primary user emulator(PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.