47 research outputs found

    Asymmetric Turbo Code for Coded-Cooperative Wireless Communication Based on Matched Interleaver with Channel Estimation and Multi-Receive Antennas at the Destination

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    This paper investigates the multiple relay coded-cooperation scheme based on asymmetric turbo code (ATC) with multiple receive antennas over Rayleigh block fading channels. An encoding scheme based on ATC is proposed for coded-cooperation i.e. distributed asymmetric turbo code (DATC). The code matched interleaver (CMI) is selected by a rigorous comparison with a uniform-random interleaver (URI). This optimum choice of interleaver at the relay nodes provides maximum benefit from DATC coded-cooperation scheme. Practically in any wireless communication system, the channel side information (CSI) is usually unknown at the receiver. Therefore, spatial normalized least mean square (NLMS) adaptive transversal filters are employed to estimate the CSI at the destination node. Moreover, in coded-cooperation scheme, the effectiveness and validation of spatial NLMS adaptive transversal filters is also verified by simulation results. Quadrature phase shift keying (QPSK) is used in coded-cooperation scheme and corresponding soft-demodulators are employed along with joint iterative soft-input soft-output (SISO) decoder at the destination node. Monte Carlo simulations shows that the proposed scheme incorporates coding gain, diversity gain and cooperation gain successfully, which eventually results in net gain of 2.7 to 3.5 dBs over non-cooperation ATC counterpart

    LDPC code-based bandwidth efficient coding schemes for wireless communications

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    This dissertation deals with the design of bandwidth-efficient coding schemes with Low-Density Parity-Check (LDPC) for reliable wireless communications. Code design for wireless channels roughly falls into three categories: (1) when channel state information (CSI) is known only to the receiver (2) more practical case of partial CSI at the receiver when the channel has to be estimated (3) when CSI is known to the receiver as well as the transmitter. We consider coding schemes for all the above categories. For the first scenario, we describe a bandwidth efficient scheme which uses highorder constellations such as QAM over both AWGN as well as fading channels. We propose a simple design with LDPC codes which combines the good properties of Multi-level Coding (MLC) and bit-interleaved coded-modulation (BICM) schemes. Through simulations, we show that the proposed scheme performs better than MLC for short-medium lengths on AWGN and block-fading channels. For the first case, we also characterize the rate-diversity tradeoff of MIMO-OFDM and SISO-OFDM systems. We design optimal coding schemes which achieve this tradeoff when transmission is from a constrained constellation. Through simulations, we show that with a sub-optimal iterative decoder, the performance of this coding scheme is very close to the optimal limit for MIMO (flat quasi-static fading), MIMO-OFDM and SISO OFDM systems. For the second case, we design non-systematic Irregular Repeat Accumulate (IRA) codes, which are a special class of LDPC codes, for Inter-Symbol Interference (ISI) fading channels when CSI is estimated at the receiver. We use Orthogonal Frequency Division Multiplexing (OFDM) to convert the ISI fading channel into parallel flat fading subchannels. We use a simple receiver structure that performs iterative channel estimation and decoding and use non-systematic IRA codes that are optimized for this receiver. This combination is shown to perform very close to a receiver with perfect CSI and is also shown to be robust to change in the number of channel taps and Doppler. For the third case, we look at bandwidth efficient schemes for fading channels that perform close to capacity when the channel state information is known at the transmitter as well as the receiver. Schemes that achieve capacity with a Gaussian codebook for the above system are already known but not for constrained constellations. We derive the near-optimum scheme to achieve capacity with constrained constellations and then propose coding schemes which perform close to capacity. Through linear transformations, a MIMO system can be converted into non-interfering parallel subchannels and we further extend the proposed coding schemes to the MIMO case too

    Adaptive MIMO Channel Estimation Utilizing Modern Channel Codes

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    Distributed Turbo Product Coding Techniques Over Cooperative Communication Systems

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    In this dissertation, we propose a coded cooperative communications framework based on Distributed Turbo Product Code (DTPC). The system uses linear block Extended Bose-Chaudhuri-Hochquenghem (EBCH) codes as component codes. The source broadcasts the EBCH coded frames to the destination and nearby relays. Each relay constructs a product code by arranging the corrected bit sequences in rows and re-encoding them vertically using EBCH as component codes to obtain an Incremental Redundancy (IR) for source\u27s data. Under this frame, we have investigated a number of interesting and important issues. First, to obtain, independent vertical parities from each relay in the same code space, we propose circular interleaving of the decoded EBCH rows before reencoding vertically. We propose and derive a novel soft information relay for the DTPC over cooperative network based on EBCH component codes. The relay generates Log-Likelihood Ratio (LLR) values for the decoded rows are used to construct a product code by re-encoding the matrix along the columns using a novel soft block encoding technique to obtain soft parity bits with different reliabilities that can be used as soft IR for source\u27s data which is forwarded to the destination. To minimize the overall decoding errors, we propose a power allocation method for the distributed encoded system when the channel attenuations for the direct and relay channels are known. We compare the performance of our proposed power allocation method with the fixed power assignments for DTPC system. We also develop a power optimization algorithm to check the validity of our proposed power allocation algorithm. Results for the power allocation and the power optimization prove on the potency of our proposed power allocation criterion and show the maximum possible attainable performance from the DTPC cooperative system. Finally, we propose new joint distributed Space-Time Block Code (STBC)-DTPC by generating the vertical parity on the relay and transmitting it to the destination using STBC on the source and relay. We tested our proposed system in a fast fading environment on the three channels connecting the three nodes in the cooperative network

    Bandwidth-efficient communication systems based on finite-length low density parity check codes

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    Low density parity check (LDPC) codes are linear block codes constructed by pseudo-random parity check matrices. These codes are powerful in terms of error performance and, especially, have low decoding complexity. While infinite-length LDPC codes approach the capacity of communication channels, finite-length LDPC codes also perform well, and simultaneously meet the delay requirement of many communication applications such as voice and backbone transmissions. Therefore, finite-length LDPC codes are attractive to employ in low-latency communication systems. This thesis mainly focuses on the bandwidth-efficient communication systems using finite-length LDPC codes. Such bandwidth-efficient systems are realized by mapping a group of LDPC coded bits to a symbol of a high-order signal constellation. Depending on the systems' infrastructure and knowledge of the channel state information (CSI), the signal constellations in different coded modulation systems can be two-dimensional multilevel/multiphase constellations or multi-dimensional space-time constellations. In the first part of the thesis, two basic bandwidth-efficient coded modulation systems, namely LDPC coded modulation and multilevel LDPC coded modulation, are investigated for both additive white Gaussian noise (AWGN) and frequency-flat Rayleigh fading channels. The bounds on the bit error rate (BER) performance are derived for these systems based on the maximum likelihood (ML) criterion. The derivation of these bounds relies on the union bounding and combinatoric techniques. In particular, for the LDPC coded modulation, the ML bound is computed from the Hamming distance spectrum of the LDPC code and the Euclidian distance profile of the two-dimensional constellation. For the multilevel LDPC coded modulation, the bound of each decoding stage is obtained for a generalized multilevel coded modulation, where more than one coded bit is considered for level. For both systems, the bounds are confirmed by the simulation results of ML decoding and/or the performance of the ordered-statistic decoding (OSD) and the sum-product decoding. It is demonstrated that these bounds can be efficiently used to evaluate the error performance and select appropriate parameters (such as the code rate, constellation and mapping) for the two communication systems.The second part of the thesis studies bandwidth-efficient LDPC coded systems that employ multiple transmit and multiple receive antennas, i.e., multiple-input multiple-output (MIMO) systems. Two scenarios of CSI availability considered are: (i) the CSI is unknown at both the transmitter and the receiver; (ii) the CSI is known at both the transmitter and the receiver. For the first scenario, LDPC coded unitary space-time modulation systems are most suitable and the ML performance bound is derived for these non-coherent systems. To derive the bound, the summation of chordal distances is obtained and used instead of the Euclidean distances. For the second case of CSI, adaptive LDPC coded MIMO modulation systems are studied, where three adaptive schemes with antenna beamforming and/or antenna selection are investigated and compared in terms of the bandwidth efficiency. For uncoded discrete-rate adaptive modulation, the computation of the bandwidth efficiency shows that the scheme with antenna selection at the transmitter and antenna combining at the receiver performs the best when the number of antennas is small. For adaptive LDPC coded MIMO modulation systems, an achievable threshold of the bandwidth efficiency is also computed from the ML bound of LDPC coded modulation derived in the first part

    On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

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    Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed

    Low Density Graph Codes And Novel Optimization Strategies For Information Transfer Over Impaired Medium

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    Effective methods for information transfer over an imperfect medium are of great interest. This thesis addresses the following four topics involving low density graph codes and novel optimization strategies.Firstly, we study the performance of a promising coding technique: low density generator matrix (LDGM) codes. LDGM codes provide satisfying performance while maintaining low encoding and decoding complexities. In the thesis, the performance of LDGM codes is extracted for both majority-rule-based and sum-product iterative decoding algorithms. The ultimate performance of the coding scheme is revealed through distance spectrum analysis. We derive the distance spectral for both LDGM codes and concatenated LDGM codes. The results show that serial-concatenated LDGM codes deliver extremely low error-floors. This work provides valued information for selecting the parameters of LDGM codes. Secondly, we investigate network-coding on relay-assisted wireless multiple access (WMA) networks. Network-coding is an effective way to increase robustness and traffic capacity of networks. Following the framework of network-coding, we introduce new network codes for the WMA networks. The codes are constructed based on sparse graphs, and can explore the diversities available from both the time and space domains. The data integrity from relays could be compromised when the relays are deployed in open areas. For this, we propose a simple but robust security mechanism to verify the data integrity.Thirdly, we study the problem of bandwidth allocation for the transmission of multiple sources of data over a single communication medium. We aim to maximize the overall user satisfaction, and formulate an optimization problem. Using either the logarithmic or exponential form of satisfaction function, we derive closed-form optimal solutions, and show that the optimal bandwidth allocation for each type of data is piecewise linear with respect to the total available bandwidth. Fourthly, we consider the optimization strategy on recovery of target spectrum for filter-array-based spectrometers. We model the spectrophotometric system as a communication system, in which the information content of the target spectrum is passed through distortive filters. By exploiting non-negative nature of spectral content, a non-negative least-square optimal criterion is found particularly effective. The concept is verified in a hardware implemen
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