This paper shows the strong converse and the dispersion of memoryless channels with cost constraints and performs a refined analysis of the third-order term in the asymptotic expansion of the maximum achievable channe...
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This paper shows the strong converse and the dispersion of memoryless channels with cost constraints and performs a refined analysis of the third-order term in the asymptotic expansion of the maximum achievable channelcoding rate, showing that it is equal to (1/2)((log n)/n) in most cases of interest. The analysis is based on a nonasymptotic converse bound expressed in terms of the distribution of a random variable termed the b-tilted information density, which plays a role similar to that of the d-tilted information in lossy sourcecoding. We also analyze the fundamental limits of lossy joint-source-channelcoding over channels with cost constraints.
We consider the problem of channel state amplification in a Gaussian channel with additive Gaussian channel states, where the encoder observes noncausally a noisy version of these states. A complete characterization i...
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We consider the problem of channel state amplification in a Gaussian channel with additive Gaussian channel states, where the encoder observes noncausally a noisy version of these states. A complete characterization is provided for the minimum reconstruction distortion under a transmitter power constraint, and it is shown that a simple analog scheme with power control is optimal. More precisely, if the power available to the encoder is below certain threshold, the analog scheme using full power is optimal, however, when the power available to the encoder is above that threshold, analog transmission using only a fixed amount of the available power is optimal. Furthermore, the problem of simultaneous message transmission and Gaussian state amplification with noisy observations is studied, for which an inner bound and two nontrivial outer bounds to the optimal tradeoff between the transmission rate and the state reconstruction distortion are provided. The coding scheme underlying the inner bound combines analog signaling and Gelfand-Pinsker coding, where the latter deviates from the operating point of Costa's dirty paper coding. The first outer bound is obtained by extending the channel decomposition technique, while the second outer bound requires a strategic analysis of the covariance matrix of the relevant random variables.
This paper considers the Softcast jointsource-channel video coding scheme for data transmission over parallel channels with different power constraints and noise characteristics, typical in DSL or PLT channels. To mi...
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ISBN:
(纸本)9781467399623
This paper considers the Softcast jointsource-channel video coding scheme for data transmission over parallel channels with different power constraints and noise characteristics, typical in DSL or PLT channels. To minimize the mean square error at receiver, an optimal precoding matrix design problem has to be solved, which requires the solution of an inverse eigenvalue problem. Such solution is taken from the MIMO channel precoder design literature. Alternative suboptimal precoding matrices are also proposed and analyzed, showing the efficiency of the optimal precoding matrix within Softcast, which provides gains increasing with the encoded video quality.
One of the main challenges for continued wireless capacity growth is the difficulty in exploiting the multicast nature of the wireless medium: wireless end points rarely experience the same channel conditions or acces...
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ISBN:
(纸本)9781479966653
One of the main challenges for continued wireless capacity growth is the difficulty in exploiting the multicast nature of the wireless medium: wireless end points rarely experience the same channel conditions or access the same content at the same time. In this paper, we present and analyze a novel wireless video delivery paradigm based on the combined use of channel-aware caching and coded multicasting that allows simultaneously serving multiple cache-enabled access points that may be requesting different content and experiencing different channel conditions. To this end, we reformulate the caching-aided coded multicast problem as a joint source-channel coding problem and design an achievable scheme that preserves the cache-enabled multiplicative throughput gains of the error-free scenario, by guaranteeing per-receiver (access point) rates unaffected by the presence of receivers with worse channel conditions.
We study the problem of communicating a distributed correlated memoryless source over a memoryless network, from source nodes to destination nodes, under quadratic distortion constraints. We establish the following tw...
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We study the problem of communicating a distributed correlated memoryless source over a memoryless network, from source nodes to destination nodes, under quadratic distortion constraints. We establish the following two complementary results: 1) for an arbitrary memoryless network, among all distributed memoryless sources of a given correlation, Gaussian sources are least compressible, that is, they admit the smallest set of achievable distortion tuples and 2) for any memoryless source to be communicated over a memoryless additive-noise network, among all noise processes of a given correlation, Gaussian noise admits the smallest achievable set of distortion tuples. We establish these results constructively by showing how schemes for the corresponding Gaussian problems can be applied to achieve similar performance for (source or noise) distributions that are not necessarily Gaussian but have the same covariance.
Two outer bounds on the admissible source region for broadcast channels with correlated sources are presented: the first one is strictly tighter than the existing outer bound by Gohari and Anantharam, while the second...
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Two outer bounds on the admissible source region for broadcast channels with correlated sources are presented: the first one is strictly tighter than the existing outer bound by Gohari and Anantharam, while the second one provides a complete characterization of the admissible source region in the case where the two sources are conditionally independent given the common part. These outer bounds are deduced from the general necessary conditions established for the lossy source broadcast problem via suitable comparisons between the virtual broadcast channel (induced by the source and the reconstructions) and the physical broadcast channel.
In jointsource-channel arithmetic coding, a forbidden symbol (FS) is added to the symbol set to make it more robust against transmission errors. By splitting the interval occupied by the FS into subintervals, various...
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ISBN:
(纸本)9781479953424
In jointsource-channel arithmetic coding, a forbidden symbol (FS) is added to the symbol set to make it more robust against transmission errors. By splitting the interval occupied by the FS into subintervals, various configurations are possible. In this paper, the delay probability function (DPF), the probability of the number of bits required to detect an error, is calculated for various FS configurations. A figure of merit is also proposed for optimizing the FS configuration. It determines the probability of missed error detection (PMD). Simulations are carried out by employing a breadth-first suboptimal sequential MAP. The simulation results show the effectiveness of the proposed figure of merit, and support the FS configuration in which the FS interval lies entirely between the other information carrying symbols to be the best.
The problem of sending two correlated vector Gaussian sources over a bandwidth-matched two-user scalar Gaussian broadcast channel is studied in this paper, where each receiver wishes to reconstruct its target source u...
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The problem of sending two correlated vector Gaussian sources over a bandwidth-matched two-user scalar Gaussian broadcast channel is studied in this paper, where each receiver wishes to reconstruct its target source under a covariance distortion constraint. We derive a lower bound on the optimal tradeoff between the transmit power and the achievable reconstruction distortion pair. Our derivation is based on a new bounding technique which involves the introduction of appropriate remote sources. Furthermore, it is shown that this lower bound is achievable by a class of hybrid schemes for the special case, where the weak receiver wishes to reconstruct a scalar source under the mean squared error distortion constraint.
In wireless sensor networks, various applications involve learning one or multiple functions of the measurements observed by sensors, rather than the measurements themselves. This paper focuses on the class of type-th...
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In wireless sensor networks, various applications involve learning one or multiple functions of the measurements observed by sensors, rather than the measurements themselves. This paper focuses on the class of type-threshold functions, e.g., the maximum and the indicator functions. A simple network model capturing both the broadcast and superposition properties of wireless channels is considered: the collocated Gaussian network. A general multiround coding scheme exploiting superposition and interaction (through broadcast) is developed. Through careful scheduling of concurrent transmissions to reduce redundancy, it is shown that given any independent measurement distribution, all type-threshold functions can be computed reliably with a nonvanishing rate in the collocated Gaussian network, even if the number of sensors tends to infinity.
The optimal energy allocations for minimizing the joint symbol error rate for binary signaling of two correlated sources over the orthogonal multiple-access Gaussian channel under joint maximum a priori (MAP) detectio...
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The optimal energy allocations for minimizing the joint symbol error rate for binary signaling of two correlated sources over the orthogonal multiple-access Gaussian channel under joint maximum a priori (MAP) detection are determined. An exact expression for the system's probability of joint symbol error, as well as its union bound, is derived. Analytic minimization of the union bound reveals that the optimal energy allocation coincides with that of nonuniform binary signaling over the single-user additive white Gaussian noise channel. It is also shown numerically that the optimal energies that minimize the union bound also minimize the exact probability of error. Finally, it is shown via simulations for strongly biased sources that the use of joint MAP detection over two independent single-user systems leads to significant gains.
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