Ming-Xian Chang

Bio: Ming-Xian Chang is an academic researcher from National Cheng Kung University. The author has contributed to research in topics: Orthogonal frequency-division multiplexing & Communication channel. The author has an hindex of 10, co-authored 39 publications receiving 494 citations. Previous affiliations of Ming-Xian Chang include King Abdulaziz University & National Chiao Tung University.

Model-based channel estimation for OFDM signals in Rayleigh fading

Abstract: This paper proposes a robust pilot-assisted channel estimation method for orthogonal frequency division multiplexing (OFDM) signals in Rayleigh fading. Our estimation method is based on nonlinear regression channel models. Unlike the linear minimum mean-squared error (LMMSE) channel estimate, the method proposed does not have to know or estimate channel statistics like the channel correlation matrix and the average signal-to-noise ratio (SNR) per bit. Numerical results indicate that the performance of the proposed channel estimator is very close to the theoretical bit error propagation lower bound that is obtained by a receiver with perfect channel response information.

Performance analysis of equalized OFDM systems in Rayleigh fading

Abstract: Channel estimation is usually needed to compensate for the amplitude and phase distortions associated with a received orthogonal frequency-division multiplexing (OFDM) waveform. This paper presents a systematic approach for analyzing the bit-error probability (BEP) of equalized OFDM signals in Rayleigh fading. Closed-form expressions for BEP performance of various signal constellations [phase-shift keying (PSK), differential phase-shift keying (DPSK), quaternary phase-shift keying (QPSK)] are provided for receivers that use a linear pilot-assisted channel estimate. We also derive the optimal linear channel estimates that yield the minimum BEP and show that some previous known results are special cases of our general formulae. The results obtained here can be applied to evaluate the performance of equalized single-carrier narrowband systems as well.

A Novel Algorithm of Inter-Subchannel Interference Self-Cancellation for OFDM Systems

Abstract: Time-varying multipath channels distort the orthogonality between subchannels in orthogonal frequency-division multiplexing (OFDM) transmission. The loss of sub-channel orthogonality causes inter-subchannel interference (ICI), which limits the achievable bit-error probability (BEP) at high signal-to-noise ratio (SNR). In this paper, we propose a simple but very effective ICI self-cancellation algorithm. A pre-processor and a post-processor arc inserted in the transmitter and receiver, respectively. The pre-processor adds diversity to the frequency- domain symbols by time-domain periodical extension, while the post-processor uses this diversity to make most of the ICI self- cancelled. Our algorithm can provide a trade-off between ICI reduction and system throughput by adjusting the length of periodical extension. For the full-extension scheme, we show that the ICI can be completely removed if the channel variation of each path is linear with time within one extended symbol interval. We further propose an equivalent implementation of the post-processor such that the complexity of the receiver is the same as the standard OFDM receiver. This implementation also enables our algorithm to be readily combined with other OFDM algorithms of channel estimation, synchronization, coding, and so on that do not consider the ICI effect. Applying the proposed algorithm of ICI reduction makes these algorithms more applicable in fast-fading channels. To provide more insight on the ICI cancellation, we derive the equivalent channel effect of our algorithm. We also analyze the variance of ICI and observe the density function of the residual ICI in our algorithm, based on which we show a procedure to derive a BEP upper bound. The proposed algorithm is further validated by simulation and the comparison with another ICI self-cancellation algorithm.

Blind and semiblind detections of OFDM signals in fading channels

Abstract: This paper considers the problem of blind joint channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) systems in a fading environment. Employing a regression model for a time-varying channel, we convert the problem into one that finds the data sequence x whose associated least-squares (LS) channel estimate z(x) is closest to the space of some regression curves (surfaces). We apply the branch-and-bound principle to solve the nonlinear integer programming problem associated with finding the curve that fits a subchannel in the LS sense. A recursive formula for fast metric update is obtained by exploiting the intrinsic characteristic of our objective function. The impacts of reordering the data sequence and selective detection are addressed. By employing a preferred order along with a selective detection method, we greatly reduce the detector complexity while giving up little performance loss. Both the complete and the reduced-complexity algorithms can be used for blind and semiblind detections of OFDM signals in a subchannel-by-subchannel manner. To further reduce the complexity and exploit the frequency-domain channel correlation, we suggest a two-stage approach that detects a few selected positions in some subchannels first, and then, treating the detected symbols as pilots, determines the remaining symbols within a properly chosen time-frequency block by a two-dimensional model-based pilot-assisted algorithm. The proposed methods do not require the information of the channel statistics like signal-to-noise ratio or channel correlation function. Performance of differential modulations like differential quaternary phase-shift keying and STAR 16-ary quadrature amplitude modulation are provided. Both blind and semiblind schemes yield satisfactory performance.

A new derivation of least-squares-fitting principle for OFDM channel estimation

Abstract: Many channel estimation and data detection algorithms of the orthogonal frequency division multiplexing (OFDM) system have been proposed. Some of these algorithms are based on the principle of linear minimum mean-square error (LMMSE) estimation, which is theoretically optimal. There are also some algorithms developed based on the least-squares-fitting (LSF) principle, which finds a regression polynomial to fit a block of tentative channel estimates in the least-squares sense. The LSF principle is a non-statistical approach, while the LMMSE algorithm is statistical and it needs to known or estimate the channel statistics like correlation matrices and signal-to-noise ratio (SNR). This letter proposes a novel viewpoint of the LSF principle. We show that the non-statistical LSF principle can be derived alternatively from the statistical LMMSE principle by eigenvector approximation. This constructs a link between these two principles. The mean-square estimation error (MSEE) analysis shows that there are common terms in the MSEE expressions of these two principles. This further validates the constructed link. Based on the derived link and MSEE analysis, we also give some characteristics and discussions of the LSF principle.

Channel estimation for wireless ofdm systems

Abstract: Techniques are described for efficiently estimating and compensating for the effects of a communication channel in a multi-carrier wireless communication system. The techniques exploit the fact that the transmitted symbols are drawn from a finite-alphabet to efficiently estimate the propagation channel for multi-carrier communication systems, such systems using OFDM modulation. A transmitter transmits data through a communication channel according to the modulation format. A receiver includes a demodulator to demodulate the data and an estimator to estimate the channel based on the demodulated data. The channel estimator applies a power-law operation to the demodulated data to identify the channel. The techniques can be used in both blind and semi-blind modes of channel estimation.

Quadrature Amplitude Modulation: From Basics to Adaptive Trellis-Coded, Turbo-Equalised and Space-Time Coded OFDM, CDMA and MC-CDMA Systems

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Channel Estimation for OFDM

Abstract: Orthogonal frequency division multiplexing (OFDM) has been widely adopted in modern wireless communication systems due to its robustness against the frequency selectivity of wireless channels. For coherent detection, channel estimation is essential for receiver design. Channel estimation is also necessary for diversity combining or interference suppression where there are multiple receive antennas. In this paper, we will present a survey on channel estimation for OFDM. This survey will first review traditional channel estimation approaches based on channel frequency response (CFR). Parametric model (PM)-based channel estimation, which is particularly suitable for sparse channels, will be also investigated in this survey. Following the success of turbo codes and low-density parity check (LDPC) codes, iterative processing has been widely adopted in the design of receivers, and iterative channel estimation has received a lot of attention since that time. Iterative channel estimation will be emphasized in this survey as the emerging iterative receiver improves system performance significantly. The combination of multiple-input multiple-output (MIMO) and OFDM has been widely accepted in modern communication systems, and channel estimation in MIMO-OFDM systems will also be addressed in this survey. Open issues and future work are discussed at the end of this paper.

Vehicular Communications: A Physical Layer Perspective

Abstract: Vehicular communications have attracted more and more attention recently from both industry and academia due to their strong potential to enhance road safety, improve traffic efficiency, and provide rich on-board information and entertainment services. In this paper, we discuss fundamental physical layer issues that enable efficient vehicular communications and present a comprehensive overview of the state-of-the-art research. We first introduce vehicular channel characteristics and modeling, which are the key underlying features differentiating vehicular communications from other types of wireless systems. We then present schemes to estimate the time-varying vehicular channels and various modulation techniques to deal with high-mobility channels. After reviewing resource allocation for vehicular communications, we discuss the potential to enable vehicular communications over the millimeter wave bands. Finally, we identify the challenges and opportunities associated with vehicular communications.

Error probability minimizing pilots for OFDM with M-PSK modulation over Rayleigh-fading channels

Abstract: Orthogonal frequency division multiplexing (OFDM) with pilot symbol assisted channel estimation is a promising technique for high rate transmissions over wireless frequency-selective fading channels. In this paper, we analyze the symbol error rate (SER) performance of OFDM with M-ary phase-shift keying (M-PSK) modulation over Rayleigh-fading channels, in the presence of channel estimation errors. Both least-squares error (LSE) and minimum mean-square error (MMSE) channel estimators are considered. For prescribed power, our analysis not only yields exact SER formulas, but also quantifies the performance loss due to channel estimation errors. We also optimize the number of pilot symbols, the placement of pilot symbols, and the power allocation between pilot and information symbols, to minimize this loss, and thereby minimize SER. Simulations corroborate our SER performance analysis, and numerical results are presented to illustrate our optimal claims.