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Title: Modelling, detection and mitigation of impulsive noise and narrowband interference for indoor broadband power line communication
Author: Yin, Jun
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2017
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Broadband power line communication (PLC) is a promising technology for the convergence of Internet, data and video for indoor networking. Impulsive noise (IN) and narrowband interference (NBI) are crucial affecting factors of the PLC system performance and cause harmful pollution to the PLC spectrum. In this thesis, a thorough study of IN and NBI is presented ranging from measurement, modelling, detection and mitigation techniques, and performance analysis. In the first contribution, the modelling of aperiodic IN for PLC is investigated. To the best of our knowledge, this is the first work to model the correlation between consecutive impulses for PLC, using a hybrid model which includes the weighted contributions of deterministic and random patterns of individual impulses in a burst. The occurrence dependence between bursts and between impulses in a burst is described by a two-level Markov Chain (MC) based model. An intensive performance analysis of the proposed models is provided. The effectiveness of the models is verified by measured results. In the second contribution, the modelling of radio NBI for PLC is investigated. A novel three-dimensional (3D) MC based statistical model is developed, to model the occurrence of NBI which is associated with the behaviours of certain radio users. An intensive performance analysis on the impact of the NBI on PLC is provided. The effectiveness of the proposed model is verified by measured results. The 3D MC model can be used for optimising cognitive PLC networks. In the third contribution, detection and mitigation of aperiodic IN over uncoded orthogonal frequency division multiplexing (OFDM) PLC systems is investigated. A null subcarriers assisted IN mitigation scheme is proposed, to mitigate IN in the scenarios of NBI absence and NBI presence, respectively. The IN vector is first reconstructed at the receiver, and then cancelled out from the received signal. Theoretical analysis shows that the proposed scheme outperforms the existing blanking method. Also, the implementation of pre-joint NBI/IN mitigation with the aid of null subcarriers in the proposed scheme can combat intensive NBI, and achieve a near-optimal bit error rate (BER) performance with no iteration. The effectiveness of the proposed mitigation scheme is verified by simulation results. In the fourth contribution, NBI detection over PLC systems is investigated. A novel higher-order statistics (HOS) based NBI detection scheme is proposed for cognitive PLC systems. In particular, the presence of IN is addressed for NBI detection, which was not considered in the previous work. An intensive performance analysis is provided, including the NBI detection probability and system capacity. The proposed NBI detection scheme outperforms the existing detection schemes and also leads to an enhanced system capacity over the existing schemes. As a conclusion, the proposed work in this thesis is applicable to the PLC systems under the disturbance of IN and NBI, and enables optimisation of system performance. In the future work, a single-carrier frequency-domain equalisation (SC-FDE) PLC system will be investigated in order to reduce the high peak-toaverage power ratio (PAPR) of signals in OFDM PLC systems. Also, different PLC channel attenuation models will be considered.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available