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Distributed video coding in wireless multimedia sensor network for multimedia broadcasting
Recently the development of Distributed Video Coding (DVC) has provided the promising theory
support to realize the infrastructure of Wireless Multimedia Sensor Network (WMSN), which composed of autonomous hardware for capturing and transmission of quality audio-visual content. The implementation of DVC in WMSN can better solve the problem of energy constraint of the sensor nodes due to the benefit of lower computational encoder in DVC. In this paper, a practical DVC scheme, pixel-domain Wyner-Ziv(PDWZ) video
coding, with slice structure and adaptive rate selection(ARS) is proposed to solve the certain problems when applying DVC into WMSN. Firstly, the proposed slice structure in PDWZ has extended the feasibility of PDWZ to work with any interleaver size used in Slepian-wolf turbo codec for heterogeneous applications. Meanwhile,
based on the slice structure, an adaptive code rate selection has been proposed aiming at reduce the system delay occurred in feedback request. The simulation results clearly showed the enhancement in R-D performance and perceptual quality. It also can be observed that system delay caused by frequent feedback is greatly reduced, which gives a promising support for WMSN with low latency and facilitates the QoS management
Turbo Decoding and Detection for Wireless Applications
A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannon’s visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon’s capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted
On Complexity, Energy- and Implementation-Efficiency of Channel Decoders
Future wireless communication systems require efficient and flexible baseband
receivers. Meaningful efficiency metrics are key for design space exploration
to quantify the algorithmic and the implementation complexity of a receiver.
Most of the current established efficiency metrics are based on counting
operations, thus neglecting important issues like data and storage complexity.
In this paper we introduce suitable energy and area efficiency metrics which
resolve the afore-mentioned disadvantages. These are decoded information bit
per energy and throughput per area unit. Efficiency metrics are assessed by
various implementations of turbo decoders, LDPC decoders and convolutional
decoders. New exploration methodologies are presented, which permit an
appropriate benchmarking of implementation efficiency, communications
performance, and flexibility trade-offs. These exploration methodologies are
based on efficiency trajectories rather than a single snapshot metric as done
in state-of-the-art approaches.Comment: Submitted to IEEE Transactions on Communication
Advanced Wireless Digital Baseband Signal Processing Beyond 100 Gbit/s
International audienceThe continuing trend towards higher data rates in wireless communication systems will, in addition to a higher spectral efficiency and lowest signal processing latencies, lead to throughput requirements for the digital baseband signal processing beyond 100 Gbit/s, which is at least one order of magnitude higher than the tens of Gbit/s targeted in the 5G standardization. At the same time, advances in silicon technology due to shrinking feature sizes and increased performance parameters alone won't provide the necessary gain, especially in energy efficiency for wireless transceivers, which have tightly constrained power and energy budgets. In this paper, we highlight the challenges for wireless digital baseband signal processing beyond 100 Gbit/s and the limitations of today's architectures. Our focus lies on the channel decoding and MIMO detection, which are major sources of complexity in digital baseband signal processing. We discuss techniques on algorithmic and architectural level, which aim to close this gap. For the first time we show Turbo-Code decoding techniques towards 100 Gbit/s and a complete MIMO receiver beyond 100 Gbit/s in 28 nm technology
Waveforms and channel coding for 5G
Abstract. The fifth generation (5G) communication systems are required to perform significantly better than the existing fourth generation (4G) systems in data rate, capacity, coverage, latency, energy consumption and cost. Hence, 5G needs to achieve considerable enhancements in the areas of bandwidth, spectral, energy, and signaling efficiencies and cost per bit. The new radio access technology (RAT) of 5G physical layer needs to utilize an efficient waveform to meet the demands of 5G. Orthogonal frequency division multiplexing (OFDM) is considered as a baseline for up to 30 GHz. However, a major drawback of OFDM systems is their large peak to average power ratio (PAPR). Here in this thesis, a simple selective-mapping (SLM) technique using scrambling is proposed to reduce the PAPR of OFDM signals. This technique selects symbol sequences with high PAPR and scrambles them until a PAPR sequence below a specific threshold is generated. The computational complexity of the proposed scheme is considerably lower than that of the traditional SLM. Also, performance of the system is investigated through simulations and more than 4.5 dB PAPR reduction is achieved. In addition, performance of single carrier waveforms is analyzed in multiple-input multiple-output (MIMO) systems as an alternative to OFDM. Performance of a single carrier massive MIMO system is presented for both uplink and downlink with single user and multiple user cases and the effect of pre-coding on the PAPR is studied. A variety of channel configurations were investigated such as correlated channels, practical channels and the channels with errors in channel estimate. Furthermore, the candidate coding schemes are investigated for the new RAT in the 5G standard corresponding the activities in the third generation partnership project (3GPP). The schemes are evaluated in terms of block error rate (BLER), bit error rate (BER), computational complexity, and flexibility. These parameters comprise a suitable set to assess the performance of different services and applications. Turbo, low density parity check (LDPC), and polar codes are considered as the candidate schemes. These are investigated in terms of obtaining suitable rates, block lengths by proper design for a fair comparison. The simulations have been carried out in order to obtain BLER / BER performance for various code rates and block lengths, in additive white Gaussian noise (AWGN) channel. Although polar codes perform well at short block lengths, LDPC has a relatively good performance at all the block lengths and code rates. In addition, complexity of the LDPC codes is relatively low. Furthermore, BLER/BER performances of the coding schemes in Rayleigh fading channels are investigated and found that the fading channel performance follows a similar trend as the performance in the AWGN channel
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