Cross Z-Complementary Pairs for Optimal Training in Spatial Modulation Over Frequency Selective Channels

The contributions of this article are twofold: Firstly, we introduce a novel class of sequence pairs, called “cross Z-complementary pairs (CZCPs),” each displaying zero-correlation zone (ZCZ) properties for both their aperiodic autocorrelation sums and crosscorrelation sums. Systematic constructions of perfect CZCPs based on selected Golay complementary pairs (GCPs) are presented. Secondly, we point out that CZCPs can be utilized as a key component in designing training sequences for broadband spatial modulation (SM) systems. We show that our proposed SM training sequences derived from CZCPs lead to optimal channel estimation performance over frequency-selective channels

Optimal Power Allocation for Channel Estimation in MIMO-OFDM System with Per-Subcarrier Transmit Antenna Selection

A novel hybrid channel estimator is proposed for multiple-input multiple-output orthogonal frequency- division multiplexing (MIMO-OFDM) system with per-subcarrier transmit antenna selection having optimal power allocation among subcarriers. In practice, antenna selection information is transmitted through a binary symmetric control channel with a crossover probability. Linear minimum mean-square error (LMMSE) technique is optimal technique for channel estimation in MIMO-OFDM system. Though LMMSE estimator performs well at low signal to noise ratio (SNR), in the presence of antenna-to-subcarrier-assignment error (ATSA), it introduces irreducible error at high SNR. We have proved that relaxed MMSE (RMMSE) estimator overcomes the performance degradation at high SNR. The proposed hybrid estimator combines the benefits of LMMSE at low SNR and RMMSE estimator at high SNR. The vector mean square error (MSE) expression is modified as scalar expression so that an optimal power allocation can be performed. The convex optimization problem is formulated and solved to allocate optimal power to subcarriers minimizing the MSE, subject to transmit sum power constraint. Further, an analytical expression for SNR threshold at which the hybrid estimator is to be switched from LMMSE to RMMSE is derived. The simulation results show that the proposed hybrid estimator gives robust performance, irrespective of ATSA error

Visualization on colour based flow vector of thermal image for movement detection during interactive session

Recently thermal imaging is exploited in applications such as motion and face detection. It has drawn attention many researchers to build such technology to improve lifestyle. This work proposed a technique to detect and identify a motion in sequence images for the application in security monitoring system or outdoor surveillance. Conventional system might cause false information with the present of shadow. Thus, methods employed in this work are Canny edge detector method, Lucas Kanade and Horn Shunck algorithms, to overcome the major problem when using thresholding method, which is only intensity or pixel magnitude is considered instead of relationships between the pixels. The results obtained could be observed in flow vector parameter and the segmentation colour based image for the time frame from 1 to 10 seconds. The visualization of both the parameters clarified the movement and changes of pixel intensity between two frames by the supportive colour segmentation, either in smooth or rough motion. Thus, this technique may contribute to others application such as biometrics, military system, and surveillance machine

Transceiver design and system optimization for ultra-wideband communications

This dissertation investigates the potential promises and proposes possible solutions to the challenges of designing transceivers and optimizing system parameters in ultra-wideband (UWB) systems. The goal is to provide guidelines for UWB transceiver implementations under constraints by regulation, existing interference, and channel estimation. New UWB pulse shapes are invented that satisfy the Federal Communications Commission spectral mask. Parameters are designed to possibly implement the proposed pulses. A link budget is quantified based on an accurate frequency-dependent path loss calculation to account for variations across the ultra-wide bandwidth of the signal. Achievable information rates are quantified as a function of transmission distance over additive white Gaussian noise and multipath channels under specific UWB constraints: limited power spectral density, specific modulation formats, and a highly dispersive channel. The effect of self-interference (SI) and inter-symbol interference (ISI) on channel capacity is determined, and modulation formats that mitigate against this effect is identified. Spreading gains of familiar UWB signaling formats are evaluated, and UWB signals are proved to be spread spectrum. Conditions are formulated for trading coding gain with spreading gain with only a small impact on performance. Numerical results are examined to demonstrate that over a frequency-selective channel, the spreading gain may be beneficial in reducing the SI and ISI resulting in higher information rates. A reduced-rank adaptive filtering technique is applied to the problem of interference suppression and optimum combining in UWB communications. The reduced-rank combining method, in particular the eigencanceler, is proposed and compared with a minimum mean square error Rake receiver. Simulation results are evaluated to show that the performance of the proposed method is superior to the minimum mean square error when the correlation matrix is estimated from limited data. Impact of channel estimation on UWB system performance is investigated when path delays and path amplitudes are jointly estimated. Cramér-Rao bound (CRB) expressions for the variance of path delay and amplitude estimates are formulated using maximum likelihood estimation. Using the errors obtained from the CRB, the effective signal-to-noise ratio for UWB Rake receivers employing maximum ratio combining (MRC) is devised in the presence of channel path delay and amplitude errors. An exact expression of the bit error rate (BER) for UWB Rake receivers with MRC is derived with imperfect estimates of channel path delays and amplitudes. Further, this analysis is applied to design optimal transceiver parameters. The BER is used as part of a binary symmetric channel and the achievable information rates are evaluated. The optimum power allocation and number of symbols allocated to the pilot are developed with respect to maximizing the information rate. The optimal signal bandwidth to be used for UWB communications is determined in the presence of imperfect channel state information. The number of multipath components to be collected by Rake receivers is designed to optimize performance with non-ideal channel estimation

A Data-Aided Channel Estimation Scheme for Decoupled Systems in Heterogeneous Networks

Uplink/downlink (UL/DL) decoupling promises more flexible cell association and higher throughput in heterogeneous networks (HetNets), however, it hampers the acquisition of DL channel state information (CSI) in time-division-duplex (TDD) systems due to different base stations (BSs) connected in UL/DL. In this paper, we propose a novel data-aided (DA) channel estimation scheme to address this problem by utilizing decoded UL data to exploit CSI from received UL data signal in decoupled HetNets where a massive multiple-input multiple-output BS and dense small cell BSs are deployed. We analytically estimate BER performance of UL decoded data, which are used to derive an approximated normalized mean square error (NMSE) expression of the DA minimum mean square error (MMSE) estimator. Compared with the conventional least square (LS) and MMSE, it is shown that NMSE performances of all estimators are determined by their signal-to-noise ratio (SNR)-like terms and there is an increment consisting of UL data power, UL data length and BER values in the SNR-like term of DA method, which suggests DA method outperforms the conventional ones in any scenarios. Higher UL data power, longer UL data length and better BER performance lead to more accurate estimated channels with DA method. Numerical results verify that the analytical BER and NMSE results are close to the simulated ones and a remarkable gain in both NMSE and DL rate can be achieved by DA method in multiple scenarios with different modulations

Soft-Decision-Driven Channel Estimation for Pipelined Turbo Receivers

We consider channel estimation specific to turbo equalization for multiple-input multiple-output (MIMO) wireless communication. We develop a soft-decision-driven sequential algorithm geared to the pipelined turbo equalizer architecture operating on orthogonal frequency division multiplexing (OFDM) symbols. One interesting feature of the pipelined turbo equalizer is that multiple soft-decisions become available at various processing stages. A tricky issue is that these multiple decisions from different pipeline stages have varying levels of reliability. This paper establishes an effective strategy for the channel estimator to track the target channel, while dealing with observation sets with different qualities. The resulting algorithm is basically a linear sequential estimation algorithm and, as such, is Kalman-based in nature. The main difference here, however, is that the proposed algorithm employs puncturing on observation samples to effectively deal with the inherent correlation among the multiple demapper/decoder module outputs that cannot easily be removed by the traditional innovations approach. The proposed algorithm continuously monitors the quality of the feedback decisions and incorporates it in the channel estimation process. The proposed channel estimation scheme shows clear performance advantages relative to existing channel estimation techniques.Comment: 11 pages; IEEE Transactions on Communications 201

Enhanced Cross Z-Complementary Set and Its Application in Generalized Spatial Modulation

Generalized spatial modulation (GSM) is a novel multiple-antenna technique offering flexibility among spectral efficiency, energy efficiency, and the cost of RF chains. In this paper, a novel class of sequence sets, called enhanced cross Zcomplementary set (E-CZCS), is proposed for efficient training sequence design in broadband GSM systems. Specifically, an E-CZCS consists of multiple CZCSs possessing front-end and tail-end zero-correlation zones (ZCZs), whereby any two distinct CZCSs have a tail-end ZCZ when a novel type of cross-channel aperiodic correlation sums is considered. The theoretical upper bound on the ZCZ width is first derived, upon which optimal E-CZCSs with flexible parameters are constructed. For optimal channel estimation over frequency-selective channels, we introduce and evaluate a novel GSM training framework employing the proposed E-CZCSs