Xianhua Dai

Linearly time-varying channel estimation for MIMO/OFDM systems using superimposed training

Channel estimation for multiple-input multiple-output/orthogonal frequency-division multiplexing (MIMO/ OFDM) systems in linearly time-varying (LTV) wireless channels using superimposed training (ST) is considered. The LTV channel is modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols. We also present a performance analysis of the channel estimation and derive a closed-form expression for the channel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST-based schemes, approach to a fixed lower-bound as the training length increases, which is directly proportional to information-pilot power ratios. To further enhance the channel estimation performance with a limited pilot power, an interference cancellation procedure is introduced to iteratively mitigate the information sequence interference to channel estimation. Simulation results show that the proposed algorithm outperforms frequency-division multiplexed training schemes.

Linearly time-varying channel estimation and symbol detection for OFDMA uplink using superimposed training

We address the problem of superimposed trainings- (STs-) based linearly time-varying (LTV) channel estimation and symbol detection for orthogonal frequency-division multiplexing access (OFDMA) systems at the uplink receiver. The LTV channel coefficients are modeled by truncated discrete Fourier bases (DFBs). By judiciously designing the superimposed pilot symbols, we estimate the LTV channel transfer functions over the whole frequency band by using a weighted average procedure, thereby providing validity for adaptive resource allocation. We also present a performance analysis of the channel estimation approach to derive a closed-form expression for the channel estimation variances. In addition, an iterative symbol detector is presented to mitigate the superimposed training effects on information sequence recovery. By the iterative mitigation procedure, the demodulator achieves a considerable gain in signal-interference ratio and exhibits a nearly indistinguishable symbol error rate (SER) performance from that of frequency-division multiplexed trainings. Compared to existing frequency-division multiplexed training schemes, the proposed algorithm does not entail any additional bandwidth while with the advantage for system adaptive resource allocation.

Linearly time-varying channel estimation and training power allocation for OFDM/MIMO systems using superimposed training

We address the problem of estimating the linearly time-varying (LTV) channel of orthogonal frequency division multiplexing (OFDM)/multiple-input multiple-output (MIMO) systems using superimposed training (ST). The LTV channel is modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols. We also present performance analysis of the channel estimation and derive a closed-form expression for the channel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST-based schemes, approach to a fixed lower-bound as the training length increases, which is directly proportional to information-pilot power ratios. For wireless communication systems with a limited transmission power, we optimize the ST power allocation by maximizing the lower bound of the average channel capacity. Simulation results show that the proposed approach outperforms the frequency-division multiplexed training schemes.

Doubly selective channel estimation for OFDM modulated amplify-and-forward relay networks using superimposed training

This article is concerned with the problem of superimposed training (ST)-aided channel estimation for orthogonal frequency division multiplexingmodulated amplify-and-forward relay networks in doubly selective environment. A ‘subblockwise’ linear assumption-based channel model is proposed to represent the mobile-to-mobile time- and frequency-selective channels. We then propose a novel ST strategy that allows the destination node to separately obtain the channel information of the source → relay link and the relay → destination link, from which the optimal ST signals are derived by minimizing the channel mean-square-error. To enhance the performance of channel estimation, a subblock tracking-based low-complexity decision feedback approach is introduced to iteratively mitigate the unknown data interference. Finally, extensive numerical results are provided to corroborate the proposed studies.

Superimposed training based doubly selective channel estimation for OFDM modulated amplify-and-forward relay networks

This paper is concerned with the problem of superimposed training based channel estimation for orthogonal frequency division multiplexing (OFDM) modulated amplify-and-forward (AF) relay networks in doubly selective environment. A `subblockwise linear assumption based channel model is proposed to represent the mobile-to-mobile doubly selective channels. We then propose novel strategy that allows the destination node to separately obtain the channel information of the source to relay link and the relay to destination link, from which the optimal ST signals are derived by minimizing the channel mean-square-error. Extensive numerical results are provided to corroborate the proposed studies.

Superimposed Training-Aided Channel Estimation for Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing Systems over High-Mobility Environment

The combination of multiple-input multiple-output (MIMO) antennas and orthogonal frequency-division multiplexing (OFDM) can achieve a lower error rate and/or enable highcapacity wireless communication systems by flexibly exploiting diversity gain and/or the spatial multiplexing gains. Such systems, however, rely upon the knowledge of propagation channels. In many mobile communication systems, transmission is impaired by both delay and Doppler spreads [1]-[7]. In such cases, explicit incorporation of the time-varying characteristics of mobile wireless channel is called for.

Iterative intercarrier interference reduction for mobile OFDM systems

For mobile applications of Orthogonal Frequency-Division Multiplexing (OFDM) systems, channel time-variations during one OFDM symbol interval results in the loss of orthogonality among subcarriers, and thus leading to intercarrier interference (ICI). This paper addresses the problem of ICI reduction for mobile OFDM systems. By rearranging the frequency-domain channel matrix, ICI can be effectively reduced by half at each iterative procedure. The advantages of the proposed scheme are shown through simulations.