Channel estimation and data detection of OFDM systems under unknown channel order doppler frequency: from point-to-point to relaying systems

Recently, there has been an increasing demand for OFDM system operating in high mobility environment. In such situation, wireless channel is both frequency-selective and time-varying, a.k.a. doubly-selective, making it hard for the receiver to keep track of the channel state information (CSI). Moreover, the statistical information of channel, e.g., tap positions, channel length, Doppler shifts and noise power, is generally unknown to the receiver. In this thesis, two kinds of mobile OFDM systems are investigated for data detection and channel estimation. Different from previous works, which highly depend on the statistical information of the doubly selective channel to deliver accurate channel estimation and data detection results, we focus on more practical scenarios with unknown channel orders and Doppler frequencies. Firstly, point-to-point OFDM system with high mobility is considered. Due to the unknown channel characteristics, we formulate the channel using GCE-BEM with a large oversampling factor. The resulted GCE-BEM coefficients are sparse on delay-Doppler domain and contain only a few nonzero elements. To enable the identification of nonzero entries, sparsity enhancing Gaussian priors with Gamma hyperpriors are adopted. An iterative algorithm is developed under variational inference (VI) framework. The proposed algorithm iteratively estimate the channel, recover the unknown data using Viterbi algorithm and learn the channel and noise statistical information, using only limited number of pilot subcarrier in one OFDM symbol. Secondly, we investigate multihop amplify-and-forward (AF) OFDM system, where system structure is generally unknown to the receiver due to the variable number of hops and relaying paths in high mobility environment. We notice that in AF relaying systems, the composite source-relay-destination channel is sufficient for data detection. Then we integrate the multilink, multihop channel matrices into one composite channel matrix, which turns out to have the same structure as the point-to-point OFDM channel. The reformulated system model is more concise and a similar iterative algorithm to that of the point-to-point case can be derived to estimate the composite channel and detect data. This means that the proposed framework applies to OFDM system under high mobility regardless of the system structure. Simulation results show that the performance of the proposed algorithm is very close to that of the optimal channel estimation and data detection algorithm, which requires specific information of system structure, channel tap positions, channel lengths, Doppler shifts as well as noise powers. It is worth noting that, the close-to-ideal performance of the proposed algorithms is achieved with none of the above information.published_or_final_versionElectrical and Electronic EngineeringMasterMaster of Philosoph