A Differential Detection Technique for Local Services in DAB Single Frequency Networks Digital Audio Broadcasting (DAB) is a widely used terrestrial audio broadcast transmission system. DAB employs Orthogonal FrequencyDivision Multiplexing which allows the operation in a Single Frequency Network (SFN). SFNs are beneficial for the distribution of services in large areas, but do not support local services, i.e. different services from different transmitters, without distortion. However, some audio service providers rely on local services. A Local Service Insertion technique for DAB SFNs that supports existing receivers was developed, tested and presented in a field trial in Braunschweig, Germany. The results showed some cochannel interference between local services for existing receivers that use conventional differential detection (CDD). In this paper, we investigate an iterative decisiondirected differential detection technique with channel equalization to combat the remaining cochannel interference. An increase in robustness against cochannel interference of about 3 dB is found in comparison to CDD.

New SemiBlind Channel Estimation for LDMLSI 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 semiblind 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.