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학술대회 New Semi-Blind Channel Estimation for LDM-LSI
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Montalban Jon, Eneko Iradier, David Romero, Pablo Angueira, 박성익, 권선형, 허남호
International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) 2019, pp.1-6
19HR2400, 초고품질 UHD (UHQ) 전송 기술 개발, 허남호
Local content insertion and viewer segmentation with proximity service information is a critical business case for broadcasting operators. This personalized service delivery will open up an opportunity for new use cases, such as local service delivery, local advertisement insertion and local emergency warning. In practice, single frequency networks (SFNs) offer a better spectrum efficiency when compared with traditional Multiple Frequency Network (MFN) approaches. Nevertheless, the addition of local content delivery can dramatically reduce that efficiency. Recently, the Layered Division Multiplexing (LDM) based Local Service Insertion (LSI) solution has been proposed as an interesting alternative for including local content in single frequency networks. Nonetheless, the required channel estimation procedure has been considered a major drawback for its successful implementation. In this work, a new semi-blind channel estimation algorithm is proposed. The algorithm takes advantage of the LDM structure and it is based on the statistical properties of the time domain Orthogonal Frequency Division Multiplexing (OFDM) frame. It proposes a solution for the major challenges that have remain unsolved so far. The paper also includes the first simulation results for this new approach.
KSP 제안 키워드
Business Case, Channel estimation(CE), Local Service Insertion, Local content delivery, Multiple frequency, New approach, Orthogonal frequency division Multiplexing(OFDM), Personalized service, Proximity Services(ProSe), Semi-blind Channel estimation, Service Information