11,202 research outputs found
A survey of digital television broadcast transmission techniques
This paper is a survey of the transmission techniques used in digital television (TV) standards worldwide. With the increase in the demand for High-Definition (HD) TV, video-on-demand and mobile TV services, there was a real need for more bandwidth-efficient, flawless and crisp video quality, which motivated the migration from analogue to digital broadcasting. In this paper we present a brief history of the development of TV and then we survey the transmission technology used in different digital terrestrial, satellite, cable and mobile TV standards in different parts of the world. First, we present the Digital Video Broadcasting standards developed in Europe for terrestrial (DVB-T/T2), for satellite (DVB-S/S2), for cable (DVB-C) and for hand-held transmission (DVB-H). We then describe the Advanced Television System Committee standards developed in the USA both for terrestrial (ATSC) and for hand-held transmission (ATSC-M/H). We continue by describing the Integrated Services Digital Broadcasting standards developed in Japan for Terrestrial (ISDB-T) and Satellite (ISDB-S) transmission and then present the International System for Digital Television (ISDTV), which was developed in Brazil by adopteding the ISDB-T physical layer architecture. Following the ISDTV, we describe the Digital Terrestrial television Multimedia Broadcast (DTMB) standard developed in China. Finally, as a design example, we highlight the physical layer implementation of the DVB-T2 standar
Sparse Signal Processing Concepts for Efficient 5G System Design
As it becomes increasingly apparent that 4G will not be able to meet the
emerging demands of future mobile communication systems, the question what
could make up a 5G system, what are the crucial challenges and what are the key
drivers is part of intensive, ongoing discussions. Partly due to the advent of
compressive sensing, methods that can optimally exploit sparsity in signals
have received tremendous attention in recent years. In this paper we will
describe a variety of scenarios in which signal sparsity arises naturally in 5G
wireless systems. Signal sparsity and the associated rich collection of tools
and algorithms will thus be a viable source for innovation in 5G wireless
system design. We will discribe applications of this sparse signal processing
paradigm in MIMO random access, cloud radio access networks, compressive
channel-source network coding, and embedded security. We will also emphasize
important open problem that may arise in 5G system design, for which sparsity
will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces
Coherent versus non-coherent decode-and-forward relaying aided cooperative space-time shift keying
Motivated by the recent concept of Space-Time Shift Keying (STSK), we propose a novel cooperative STSK family, which is capable of achieving a flexible rate-diversity tradeoff, in the context of cooperative space-time transmissions. More specifically, we first propose a Coherent cooperative STSK (CSTSK) scheme, where each Relay Node (RN) activates Decode-and-Forward (DF) transmissions, depending on the success or failure of Cyclic Redundancy Checking (CRC). We invoke a bitto- STSK mapping rule, where according to the input bits, one of the Q pre-assigned dispersion vectors is activated to implicitly convey log2(Q) bits, which are transmitted in combination with the classic log2(L)-bit modulated symbol. Additionally, we introduce a beneficial dispersion vector design, which enables us to dispense with symbol-level Inter-Relay Synchronization (IRS). Furthermore, the Destination Node (DN) is capable of jointly detecting the signals received from the source-destination and relay-destination links, using a low-complexity single-stream-based Maximum Likelihood (ML) detector, which is an explicit benefit of our Inter-Element Interference (IEI)-free system model. More importantly, as a benefit of its design flexibility, our cooperative CSTSK arrangement enables us to adapt the number of the RNs, the transmission rate as well as the achievable diversity order. Moreover, we also propose a Differentially-encoded cooperative STSK (DSTSK) arrangement, which dispenses with CSI estimation at any of the nodes, while retaining the fundamental benefits of the cooperative CSTSK scheme
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