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

Doctor of Philosophy

dissertationMultiple-input and multiple-output (MIMO) technique has emerged as a key feature for future generations of wireless communication systems. It increases the channel capacity proportionate to the minimum number of transmit and receive antennas. This dissertation addresses the receiver design for high-rate MIMO communications in at fading environments. The emphasis of the thesis is on the cases where channel state information (CSI) is not available and thus, clever channel estimation algorithms have to be developed to bene t from the maximum available channel capacity. The thesis makes four distinct novel contributions. First, we note that the conventional MCMC-MIMO detector presented in the prior work may deteriorate as SNR increases. We suggest and show through computer simulations that this problem to a great extent can be solved by initializing the MCMC detector with regulated states which are found through linear detectors. We also introduce the novel concept of staged-MCMC in a turbo receiver, where we start the detection process at a lower complexity and increase complexity only if the data could not be correctly detected in the present stage of data detection. Second, we note that in high-rate MIMO communications, joint data detection and channel estimation poses new challenges when a turbo loop is used to improve the quality of the estimated channel and the detected data. Erroneous detected data may propagate in the turbo loop and, thus, degrade the performance of the receiver signi cantly. This is referred to as error propagation. We propose a novel receiver that decorrelates channel estimation and the detected data to avoid the detrimental e ect of error propagation. Third, the dissertation studies joint channel estimation and MIMO detection over a continuously time-varying channel and proposes a new dual-layer channel estimator to overcome the complexity of optimal channel estimators. The proposed dual-layer channel estimator reduces the complexity of the MIMO detector with optimal channel estimator by an order of magnitude at a cost of a negligible performance degradation, on the order of 0.1 to 0.2 dB. The fourth contribution of this dissertation is to note that the Wiener ltering techniques that are discussed in this dissertation and elsewhere in the literature assume that channel (time-varying) statistics are available. We propose a new method that estimates such statistics using the coarse channel estimates obtained through pilot symbols. The dissertation also makes an additional contribution revealing di erences between the MCMC-MIMO and LMMSE-MIMO detectors. We nd that under the realistic condition where CSI has to be estimated, hence the available channel estimate will be noisy, the MCMC-MIMO detector outperforms the LMMSE-MIMO detector with a signi cant margin

Robust frequency-domain turbo equalization for multiple-input multiple-output (MIMO) wireless communications

This dissertation investigates single carrier frequency-domain equalization (SC-FDE) with multiple-input multiple-output (MIMO) channels for radio frequency (RF) and underwater acoustic (UWA) wireless communications. It consists of five papers, selected from a total of 13 publications. Each paper focuses on a specific technical challenge of the SC-FDE MIMO system. The first paper proposes an improved frequency-domain channel estimation method based on interpolation to track fast time-varying fading channels using a small amount of training symbols in a large data block. The second paper addresses the carrier frequency offset (CFO) problem using a new group-wise phase estimation and compensation algorithm to combat phase distortion caused by CFOs, rather than to explicitly estimate the CFOs. The third paper incorporates layered frequency-domain equalization with the phase correction algorithm to combat the fast phase rotation in coherent communications. In the fourth paper, the frequency-domain equalization combined with the turbo principle and soft successive interference cancelation (SSIC) is proposed to further improve the bit error rate (BER) performance of UWA communications. In the fifth paper, a bandwidth-efficient SC-FDE scheme incorporating decision-directed channel estimation is proposed for UWA MIMO communication systems. The proposed algorithms are tested by extensive computer simulations and real ocean experiment data. The results demonstrate significant performance improvements in four aspects: improved channel tracking, reduced BER, reduced computational complexity, and enhanced data efficiency --Abstract, page iv

Review of Recent Trends

This work was partially supported by the European Regional Development Fund (FEDER), through the Regional Operational Programme of Centre (CENTRO 2020) of the Portugal 2020 framework, through projects SOCA (CENTRO-01-0145-FEDER-000010) and ORCIP (CENTRO-01-0145-FEDER-022141). Fernando P. Guiomar acknowledges a fellowship from “la Caixa” Foundation (ID100010434), code LCF/BQ/PR20/11770015. Houda Harkat acknowledges the financial support of the Programmatic Financing of the CTS R&D Unit (UIDP/00066/2020).MIMO-OFDM is a key technology and a strong candidate for 5G telecommunication systems. In the literature, there is no convenient survey study that rounds up all the necessary points to be investigated concerning such systems. The current deeper review paper inspects and interprets the state of the art and addresses several research axes related to MIMO-OFDM systems. Two topics have received special attention: MIMO waveforms and MIMO-OFDM channel estimation. The existing MIMO hardware and software innovations, in addition to the MIMO-OFDM equalization techniques, are discussed concisely. In the literature, only a few authors have discussed the MIMO channel estimation and modeling problems for a variety of MIMO systems. However, to the best of our knowledge, there has been until now no review paper specifically discussing the recent works concerning channel estimation and the equalization process for MIMO-OFDM systems. Hence, the current work focuses on analyzing the recently used algorithms in the field, which could be a rich reference for researchers. Moreover, some research perspectives are identified.publishersversionpublishe

Physical layer authentication for wireless communications

指導教員：姜　暁