167 research outputs found

    Design of Fixed-Point Processing Based LDPC Codes Using EXIT Charts

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    Logarithmic representation of the variables processed by iterative decoding algorithms of Low-Density Parity-Check (LDPC) codes are attractive, since the resultant reduced dynamic range of its Logarithmic Likelihood Ratios (LLRs) allows a Fixed Point (FP) operand-representation to be used. This FP representation has a lower computational complexity than a floating point representation, allowing the decoder's hardware to have a low energy consumption, which depends on the Operand-Width (OW) of the LLRs. However, if the OW is too low, then an inevitable performance degradation will be introduced. Therefore it is desirable to determine the minimum OW that does not impose a significant performance degradation. Previous efforts have advocated different OWs based on results obtained using time-consuming Bit Error Ratio (BER) simulations. However, these simulations are extremely time consuming, owing to the requirement of considering a range of channel Signal-to-Noise Ratios (SNRs). Therefore, in this paper, we propose the employment of EXtrinsic Information Transfer (EXIT) charts to overcome this drawback. Furthermore, EXIT charts analysis has the additional benefit of offering insights into the specific causes of the performance degradations encountered. Finally, a FP scheme having an overall OW = 6 is proposed for the implementation of the Min-Sum Algorithm (MSA)

    Wireless information and power transfer: from scientific hypothesis to engineering practice

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    Recently, there has been substantial research interest in the subject of Simultaneous Wireless Information andPower Transfer (SWIPT) owing to its cross-disciplinary appeal and its wide-ranging application potential, whichmotivates this overview. More explicitly, we provide a brief survey of the state-of-the-art and introduce severalpractical transceiver architectures that may facilitate its implementation. Moreover, the most important link-levelas well as system-level design aspects are elaborated on, along with a variety of potential solutions and researchideas. We envision that the dual interpretation of Radio Frequency (RF) signals creates new opportunities as wellas challenges requiring substantial research, innovation and engineering efforts

    Optimum Physical-Layer Frame Size for Maximising the Application-Layer Rateless Code’s Effective Throughput

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    The tolerable packet-loss ratio of an Internet Protocol (IP) based wireless networks varies according to the specific services considered. File transfer for example must be error free but tolerates higher delays, whereas maintaining a low delay is typically more important in interactive Voice Over IP (VOIP) or video services. Classic Forward Error Correction (FEC) may be applied to the data to provide resilience against bit errors. A wireless IP network provides the opportunity for the inclusion of FEC at the physical, transport and application layers. The demarcation between the analogue and digital domain imposed at the Physical layer (PHY) predetermines the nature of the FEC scheme implemented at the various layers. At the PHY individual packets may be offered FEC protection, which increases the likelihood of their error-free insertion into the protocol stack. Higher layers receive packets that are error free and the purpose of a FEC scheme implemented here is to regenerate any missing packets obliterated for example by the Binary Erasure Channel (BEC) of the IP network’s routers. A rateless code may be beneficially employed at a higher Open Systems Interconnection (OSI) layer for replenishing the obliterated packets, but unless the characteristics of the channel are considered, the ultimate rate achieved by such a code may be compromised, as shown in this contribution

    Multi-level Turbo Decoding Assisted Soft Combining Aided Hybrid ARQ

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    Hybrid Automatic Repeat reQuest (ARQ) plays an essential role in error control. Combining the incorrectly received packet replicas in hybrid ARQ has been shown to reduce the resultant error probability, while improving the achievable throughput. Hence, in this contribution, multi-level turbo codes have been amalgamated both with hybrid ARQ and efficient soft combining techniques for taking into account the Log- Likelihood Ratios (LLRs) of retransmitted packet replicas. In this paper, we present a soft combining aided hybrid ARQ scheme based on multi-level turbo codes, which avoid the capacity loss of the twin-level turbo codes that are typically employed in hybrid ARQ schemes. More specifically, the proposed receiver dynamically appends an additional parallel concatenated Bahl, Cocke, Jelinek and Raviv (BCJR) algorithm based decoder in order to fully exploit each retransmission, thereby forming a multi-level turbo decoder. Therefore, all the extrinsic information acquired during the previous BCJR operations will be used as a priori information by the additional BCJR decoders, whilst their soft output iteratively enhances the a posteriori information generated by the previous decoding stages. We also present link- level Packet Loss Ratio (PLR) and throughput results, which demonstrate that our scheme outperforms some of the previously proposed benchmarks

    Coursework for introducing Matlab to communications engineers

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    This coursework is intended to accompany a lecture and laboratory series that introduces the syntax and operation of Matlab, possibly at the beginning of a master-level degree course on communications engineering. Owing to this, the coursework is specifically designed to have relevance to communication engineers, granting them the ability to use Matlab to design, simulate and characterize communication systems. The coursework assumes no prior knowledge or experience in communication engineering or Matlab, but is designed to be interesting and challenging to students that do have this knowledge or experience. The coursework considers the most relevant aspects of Matlab, namely matrix manipulation, programming, Monte Carlo simulation and error ratio plotting. It also requires students to design and optimize innovative solutions to problems with no single correct answer. The students may be expected to spend around 50 hours completing this coursework and they are assessed on the functionality, efficiency and human-readability of their solutions. Automated marking may be used to assess the functionality and efficiency of the solutions, leaving only the human-readability requiring manual marking. The coursework has been successfully used and refined over several years at the University of Southampton, UK

    A Vision for 5G Channel Coding

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    Channel coding is a vital but complex component of cellular communication systems, which is used for correcting the communication errors that are caused by noise, interference and poor signal strength. The turbo code was selected as the main channel code in 3G and 4G cellular systems, but the 3GPP standardization group is currently debating whether it should be replaced by the Low Density Parity Check (LDPC) code in 5G. This debate is being driven by the requirements for 5G, which include throughputs of up to 20 Gbps in the downlink to user devices, ultra-low latencies, as well as much greater flexibility to support diverse use-cases, including broadband data, Internet of Things (IoT), vehicular communications and cloud computing. In our previous white paper, we demonstrated that flexible turbo codes can achieve these requirements with superior hardware- and energy-efficiencies than flexible LDPC decoders. However, the proponents of LDPC codes have highlighted that inflexible LDPC decoders can achieve throughputs of 20 Gbps with particularly attractive hardware- and energy- efficiencies. This white paper outlines a vision for 5G, in which channel coding is provided by a flexible turbo code for most use-cases, but which is supported by an inflexible LDPC code for 20 Gbps downlink use-cases, such as fixed wireless broadband. We demonstrate that this approach can meet all of the 5G requirements, while offering hardware- and energy-efficiencies that are significantly better than those of an LDPC-only solution. Furthermore, the proposed approach benefits from synergy with the 3G and 4G turbo code, as well as a significantly faster time-to-market for 5G. These benefits translate to a 5G that is significantly more capable, significantly easier to deploy and significantly lower cost

    The 5G channel code contenders

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    Innovation in the Undergraduate Microelectronics Programmes at the University of Southampton

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    Iterative source and channel decoding relying on correlation modelling for wireless video transmission

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    Since joint source-channel decoding (JSCD) is capable of exploiting the residual redundancy in the source signals for improving the attainable error resilience, it has attracted substantial attention. Motivated by the principle of exploiting the source redundancy at the receiver, in this treatise we study the application of iterative source channel decoding (ISCD) aided video communications, where the video signal is modelled by a first-order Markov process. Firstly, we derive reduced-complexity formulas for the first-order Markov modelling (FOMM) aided source decoding. Then we propose a bit-based iterative horizontal vertical scanline model (IHVSM) aided source decoding algorithm, where a horizontal and a vertical source decoder are employed for exchanging their extrinsic information using the iterative decoding philosophy. The iterative IHVSM aided decoder is then employed in a forward error correction (FEC) encoded uncompressed video transmission scenario, where the IHVSM and the FEC decoder exchange softbit-information for performing turbo-like ISCD for the sake of improving the reconstructed video quality. Finally, we benchmark the attainable system performance against a near-lossless H.264/AVC video communication system and the existing FOMM based softbit source decoding scheme, where The financial support of the RC-UK under the auspices of the India-UK Advanced Technology Centre (IU-ATC) and that of the EU under the CONCERTO project as well as that of the European Research Council’s Advanced Fellow Grant is gratefully acknowledged. The softbit decoding is performed by a one-dimensional Markov model aided decoder. Our simulation results show that Eb=N0 improvements in excess of 2.8 dB are attainable by the proposed technique in uncompressed video applications
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