This work focuses on the construction of optimized binary signaling schemes for two-sender uncoded transmission of correlated non-uniform sources over non-orthogonal Gaussian multiple access channels. Based on an erro...
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ISBN:
(纸本)9781538663585
This work focuses on the construction of optimized binary signaling schemes for two-sender uncoded transmission of correlated non-uniform sources over non-orthogonal Gaussian multiple access channels. Based on an error-rate analysis under joint maximum-a-posteriori decoding, optimized binary-pulsed amplitude modulation constellations for two senders are derived to minimize the system's error rate. The joint probability distribution of the two-senders' source is observed to induce a special layout of optimized constellations which can effectively control the interference due to non-orthogonal transmission. Numerical results further confirm that significant gains are achievable by the proposed design.
We consider a universal jointsourcechannelcoding (JSCC) scheme to transmit an arbitrary memoryless source over an arbitrary additive channel. We adopt an architecture that consists of Gaussian codebooks for both th...
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ISBN:
(纸本)9781538647813
We consider a universal jointsourcechannelcoding (JSCC) scheme to transmit an arbitrary memoryless source over an arbitrary additive channel. We adopt an architecture that consists of Gaussian codebooks for both the source reproduction sequences and channel codewords. The natural minimum Euclidean distance encoder and decoder, however, need to be judiciously modified to ensure universality as well as to obtain the best (highest) possible communication rates. In particular, we consider the analogue of an unequal error (or message) protection scheme in which all sources are partitioned into disjoint power type classes. We also regularize the nearest neighbor decoder so an appropriate measure of the size of each power type class is taken into account in the decoding strategy. For such an architecture, we derive ensemble tight second-order asymptotics.
A joint source-channel coding system for image communication over an additive white Gaussian noise channel is presented. It employs vector quantization based hybrid, digital-analog modulation techniques with bandwidth...
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ISBN:
(纸本)0769523099
A joint source-channel coding system for image communication over an additive white Gaussian noise channel is presented. It employs vector quantization based hybrid, digital-analog modulation techniques with bandwidth compression and expansion for transmitting and reconstructing the wavelet coefficients of an image. The main advantage of the proposed system is that it achieves good performance at the design channel signal-to-noise ratio (CSNR), while still maintaining a "graceful improvement" characteristic at higher CSNRs. Comparisons are made with two purely digital systems and two purely analog systems. Simulation shows that the proposed system is superior to the other investigated systems for a wide range of CSNRs.
We propose a practical FEC code rate decision scheme based on jointsource-channel distortion model. The conventional FEC code rate decision schemes using analytical sourcecoding distortion model and channel-induced ...
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ISBN:
(纸本)9781479934324
We propose a practical FEC code rate decision scheme based on jointsource-channel distortion model. The conventional FEC code rate decision schemes using analytical sourcecoding distortion model and channel-induced distortion model are usually complex, and typically employ the process of model parameter training which involves potentially high computational complexity and implementation cost. Since the proposed joint model is expressed as a simple closed form and has a small number of scene dependent model parameters, a video sender using the model can be easily implemented. It is shown by simulations that the proposed method can accurately estimate the optimal FEC code rate with low computational complexity.
We consider a communication system in which the outputs of a Markov source are encoded and decoded in real-time by a finite memory receiver, and the distortion measure does not tolerate delays. The objective is to cho...
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ISBN:
(纸本)9781604234916
We consider a communication system in which the outputs of a Markov source are encoded and decoded in real-time by a finite memory receiver, and the distortion measure does not tolerate delays. The objective is to choose designs, i.e. realtime encoding, decoding and memory update strategies that minimize a total expected distortion measure. This is a dynamic team problem with non-classical information structure [7]. We use the structural results of [4] to develop a sequential decomposition for the finite and infinite horizon problems. Thus, we obtain a systematic methodology for the determination of jointly optimal encoding decoding and memory update strategies for real-time point-to-point communication.
In this thesis, different aspects of lattice-based precoding and decoding for the transmission of digital and analog data over MIMO fading channels are investigated:1) Lattice-based precoding in MIMO broadcast systems...
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In this thesis, different aspects of lattice-based precoding and decoding for the transmission of digital and analog data over MIMO fading channels are investigated:1) Lattice-based precoding in MIMO broadcast systems:A new viewpoint for adopting the lattice reduction in communication over MIMO broadcast channels is introduced. Lattice basis reduction helps us to reduce the average transmitted energy by modifying the region which includes the constellation points. The new viewpoint helps us to generalize the idea of lattice-reduction-aided precoding for the case of unequal-rate transmission, and obtain analytic results for the asymptotic behavior of the symbol-error-rate for the lattice-reduction-aided precoding and the perturbation technique. Also, the outage probability for both cases of fixed-rate users and fixed sum-rate is analyzed. It is shown that the lattice-reduction-aided method, using LLL algorithm, achieves the optimum asymptotic slope of symbol-error-rate (called the precoding diversity).2) Lattice-based decoding in MIMO multiaccess systems and MIMO point-to-point systems:Diversity order and diversity-multiplexing tradeoff are two important measures for the performance of communication systems over MIMO fading channels. For the case of MIMO multiaccess systems (with single-antenna transmitters) or MIMO point-to-point systems with V-BLAST transmission scheme, it is proved that lattice-reduction-aided decoding achieves the maximum receive diversity (which is equal to the number of receive antennas). Also, it is proved that the naive lattice decoding (which discards the out-of-region decoded points) achieves the maximum diversity in V-BLAST systems. On the other hand, the inherent drawbacks of the naive lattice decoding for general MIMO fading systems is investigated. It is shown that using the naive lattice decoding for MIMO systems has considerable deficiencies in terms of the diversity-multiplexing tradeoff. Unlike the case of maximum-likelihood decod
This paper proposes a new wireless video communication scheme to achieve high-efficiency video transmission over noisy channels. It exploits the idea of model division multiple access (MDMA) and extracts common semant...
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This paper extends the well-known sourcecoding problem of multiple descriptions, in its general and basic setting, to analog source-channelcoding scenarios. Encoding-decoding functions that optimally map between the...
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ISBN:
(纸本)9781479999897
This paper extends the well-known sourcecoding problem of multiple descriptions, in its general and basic setting, to analog source-channelcoding scenarios. Encoding-decoding functions that optimally map between the (possibly continuous valued) source and the channel spaces are numerically derived. The main technical tool is a non-convex optimization method, namely, deterministic annealing, which has recently been successfully used in other mapping optimization problems. The obtained functions exhibit several interesting structural properties, map multiple source intervals to the same interval in the channel space, and consistently outperform the known competing mapping techniques.
channel-optimized Index Assignment (IA) of source codewords is the simple but effective approach of improving the error resilience of the communication systems. Although IA is a type of jointsourcechannelcoding (JS...
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ISBN:
(纸本)9781509027118
channel-optimized Index Assignment (IA) of source codewords is the simple but effective approach of improving the error resilience of the communication systems. Although IA is a type of jointsourcechannelcoding (JSCC), it does not intervene with the source codec design. So, in addition to the fact that this method can be used in designing systems effectively, it can be also applied to the existing system. In the past, several methods and algorithms were developed for the IA problem. Among these IA algorithms, Simulated Annealing (SA) algorithm is the most effective and popular algorithm with fast convergence time, wide use in optimization problems in general and issue of IA problem in particular and has been continuously improved. In this paper, we focus on the MSA algorithm, one of the latest improved versions of SA for the IA problem and improved the MSA algorithm by using the mechanism of TS algorithm in order to avoid repeated searches. We also proposed the modified structure Tabu list applied to the new algorithm in order to extend the searching space and to enhance the algorithm performance. The effectiveness of the proposed method is confirmed through experiments.
In this thesis, bit-by-bit power allocation in order to minimize mean-squared error (MSE) distortion of a basic communication system is studied. This communication system consists of a quantizer. There may or may not ...
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In this thesis, bit-by-bit power allocation in order to minimize mean-squared error (MSE) distortion of a basic communication system is studied. This communication system consists of a quantizer. There may or may not be a channel encoder and a Binary Phase Shift Keying (BPSK) modulator. In the quantizer, natural binary mapping is made. First, the case where there is no channelcoding is considered. In the uncoded case, hard decision decoding is done at the receiver. It is seen that errors that occur in the more significant information bits contribute more to the distortion than less significant bits. For the uncoded case, the optimum power profile for each bit is determined analytically and through computer-based optimization methods like differential evolution. For low signal-to-noise ratio (SNR), the less significant bits are allocated negligible power compared to the more significant bits. For high SNRs, it is seen that the optimum bit-by-bit power allocation gives constant MSE gain in dB over the uniform power allocation. Second, the coded case is considered. Linear block codes like (3,2), (4,3) and (5,4) single parity check codes and (7,4) Hamming codes are used and soft-decision decoding is done at the receiver. Approximate expressions for the MSE are considered in order to find a near-optimum power profile for the coded case. The optimization is done through a computer-based optimization method (differential evolution). For a simple code like (7,4) Hamming code simulations show
that up to 3 dB MSE gain can be obtained by changing the power allocation on the
information and parity bits. A systematic method to find the power profile for linear block codes is also introduced given the knowledge of input-output weight enumerating function of the code. The information bits have the same power, and parity bits
have the same power, and the two power levels can be different.
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