We study the transmission of two correlated and memoryless sources (U-1, U-2) over several multiuser phase asynchronous channels. Namely, we consider a multiple access relay channel (MARC) with causal, and a MARC with...
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We study the transmission of two correlated and memoryless sources (U-1, U-2) over several multiuser phase asynchronous channels. Namely, we consider a multiple access relay channel (MARC) with causal, and a MARC with non-causal unidirectional cooperation between encoders, referred to as phase-incoherent causal (respectively, non-causal) cognitive MARCs. We also consider phase-incoherent interference channel models with and without relay, in the same context. In all cases, the input signals are assumed to undergo non-ergodic phase shifts, which are unknown to the transmitters and known to the receivers as a realistic assumption. Both necessary and sufficient conditions in order to reliably send the correlated sources to the destinations are derived. In particular, for all of the channel models, by using a key lemma, we first derive an outer bound for reliable communication. Then, using separate source and channelcoding and under specific gain conditions, we establish the same region as the inner bound. We thus conclude that without the knowledge of the phase shifts at transmitters, and under specific gain conditions, separation is optimal.
In this paper we provide sufficient conditions for lossy transmission of functions of correlated data over a multiple access channel (MAC). The conditions obtained can be shown as generalized version of Yamamoto's...
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ISBN:
(纸本)9781424441471
In this paper we provide sufficient conditions for lossy transmission of functions of correlated data over a multiple access channel (MAC). The conditions obtained can be shown as generalized version of Yamamoto's result [28]. We also obtain efficient joint source-channel coding schemes for transmission of discrete and continuous alphabet sources to recover the function values.
The bivariate Gaussian multiterminal sourcecoding problem with transmission over the Gaussian multiple-access channel is studied. We propose the use of low-delay jointsource-channel mappings and show how performance...
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The bivariate Gaussian multiterminal sourcecoding problem with transmission over the Gaussian multiple-access channel is studied. We propose the use of low-delay jointsource-channel mappings and show how performance saturation, which is unavoidable with linear transmission, can be overcome by optimizing the mappings. The optimized mappings are in general nonlinear and perform a combination of hard and soft decision signaling for the error-resilient transmission of analog data.
We study joint source-channel coding (JSCC) of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a framework for realizing optimum JSCC schemes that enable encoding and transmitting CS measu...
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We study joint source-channel coding (JSCC) of compressed sensing (CS) measurements using vector quantizer (VQ). We develop a framework for realizing optimum JSCC schemes that enable encoding and transmitting CS measurements of a sparse source over discrete memoryless channels, and decoding the sparse source signal. For this purpose, the optimal design of encoder-decoder pair of a VQ is considered, where the optimality is addressed by minimizing end-to-end mean square error (MSE). We derive a theoretical lower bound on the MSE performance and propose a practical encoder-decoder design through an iterative algorithm. The resulting coding scheme is referred to as channel-optimized VQ for CS, coined COVQ-CS. In order to address the encoding complexity issue of the COVQ-CS, we propose to use a structured quantizer, namely low-complexity multistage VQ (MSVQ). We derive new encoding and decoding conditions for the MSVQ and then propose a practical encoder-decoder design algorithm referred to as channel-optimized MSVQ for CS, coined COMSVQ-CS. Through simulation studies, we compare the proposed schemes vis-a-vis relevant quantizers.
Recently, a lot of research has been done on compressed sensing, capturing compressible signals using random linear projections to a space of radically lower dimension than the ambient dimension of the signal. The mai...
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ISBN:
(纸本)9781424423538
Recently, a lot of research has been done on compressed sensing, capturing compressible signals using random linear projections to a space of radically lower dimension than the ambient dimension of the signal. The main impetus of this is that the radically dimension-lowering linear projection step can be done totally in analog hardware, in some cases even in constant time, to avoid the bottleneck in sensing and quantization steps where a large number of samples need to be sensed and quantized in short order, mandating the use of it large number of fast expensive sensors and A/D converters. Reconstruction algorithms from these projections have been found that come within distortion levels comparable to the state of the art in lossy compression algorithms. This paper considers a variation on compressed sensing that makes it resistant to spiky noise. This is achieved by an analog real-field error-correction coding step. It results in a small asymptotic overhead in the number of samples, but makes exact reconstruction under spiky measurement noise, one type of which is the salt and pepper noise in imaging devices, possible. Simulations are per-formed that corroborate our claim and in fact substantially improve reconstruction under unreliable sensing characteristics and are stable even under small perturbations with Gaussian noise.
In this paper, an improved soft in soft out (SISO) iterative decoding scheme for joint source-channel coding is presented. It is realized as the iterative soft decoding of arithmetic code based on sequential decoding ...
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ISBN:
(纸本)9781479934324
In this paper, an improved soft in soft out (SISO) iterative decoding scheme for joint source-channel coding is presented. It is realized as the iterative soft decoding of arithmetic code based on sequential decoding to successively prune the decoding tree. Making use of the forecasted forbidden symbols, an error-resistant arithmetic code with an improved a posteriori probability (APP) metric is adopted to further enhance the error correction performance. Simulation results have validated the superiority of our scheme in terms of packet error rate for the AWGN channel.
We consider the joint source-channel coding (JSCC) problem where the real valued outputs of two correlated memoryless Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying any error co...
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ISBN:
(纸本)9781479944491
We consider the joint source-channel coding (JSCC) problem where the real valued outputs of two correlated memoryless Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying any error correcting code, over a multiple access channel (MAC) which consists of two orthogonal point-to-point time-correlated Rayleigh fading sub-channels with soft-decision demodulation. At the receiver side, a joint sequence maximum a posteriori (MAP) detector is used to exploit the correlation between the two sources as well as the redundancy left in the quantizer's indices, the channel's soft-decision outputs, and noise memory. The MAC's sub-channels are modeled via non-binary Markov noise discrete channels recently shown to effectively represent point-to-point fading channels. For the simple case of quantizing the sources with two levels, we establish a necessary and sufficient condition under which the joint sequence MAP decoder can be reduced to a simple instantaneous symbol-by-symbol decoder. Then, using numerical results obtained by system simulation, it is observed that when the sources are highly correlated and soft-decision quantization is used, JSCC can profit from a high correlation in the channel noise process and provide significant signal-to-distortion ratio improvements of up to 6.3 dB over a fully interleaved channel.
This paper investigates the application of novel packet loss protection schemes to compress mixtures of speech sources for interactive real-time audio services such as spatial teleconferencing. Hybrid Forward Error Co...
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ISBN:
(纸本)9781479954032
This paper investigates the application of novel packet loss protection schemes to compress mixtures of speech sources for interactive real-time audio services such as spatial teleconferencing. Hybrid Forward Error Correction (FEC) and Multiple Description coding (MDC) packet loss protection techniques are applied to the outputs of a psychoacoustic-based Analysis-By-Synthesis (PABS) coder designed for such applications. The protection approaches split the coder outputs into two descriptions that are separately protected using the hybrid FEC-MDC techniques. Perceptual Evaluation of Speech Quality (PESQ) measurements compare the performance of different protection schemes for a range of typical packet loss conditions. Results indicate the proposed scheme maintains the perceptual quality of the speech sources across a wide variety of packet loss conditions.
In this paper, we proposed a double-level error resilient joint source-channel coding scheme for image transmission. Characteristically, we inserted one coordinative component named error resilient entropy coding (ERE...
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ISBN:
(纸本)9781424450053
In this paper, we proposed a double-level error resilient joint source-channel coding scheme for image transmission. Characteristically, we inserted one coordinative component named error resilient entropy coding (EREC) between sourcecoding and channelcoding to achieve additional error resilient capability. Based on the novel architecture, we proved that, in the aspects of computational complexity, coding redundancy and furthermore the decoding performance of image transmission, our scheme outperformed either separate source and channelcoding scheme or joint source-channel coding scheme with synchronization words.
In this paper, the problem of transmitting an analog Gaussian source over an additive white Gaussian noise (AWGN) channel in the presence of a Gaussian interference known only at the transmitter is investigated. Our g...
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ISBN:
(纸本)9781479953592
In this paper, the problem of transmitting an analog Gaussian source over an additive white Gaussian noise (AWGN) channel in the presence of a Gaussian interference known only at the transmitter is investigated. Our goal is to estimate both the analog source and the channel state at the receiver simultaneously. In this work, we present different transmission schemes based on joint source-channel coding. We study hybrid digital-analog (HDA) joint source-channel coding schemes and analyze the region of (mean-squared error) distortion pairs (in estimating the source and the state) that are simultaneously achievable.
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