This paper deals with codes that combine source and channel encoding operations. After discussing the potential usefulness of these variable-length error correcting (VLEC) codes, necessary conditions on their length d...
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ISBN:
(纸本)0780377990
This paper deals with codes that combine source and channel encoding operations. After discussing the potential usefulness of these variable-length error correcting (VLEC) codes, necessary conditions on their length distribution are established. It is shown that, depending on the targetted application, several families of VLEC codes can be defined, whose conditions of existence differ.
Federated learning (FL) is an edge learning framework that has received significant attention recently. However, the cost of communication has become a major challenge for FL as the number of edge devices grows and th...
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ISBN:
(纸本)9798350329285
Federated learning (FL) is an edge learning framework that has received significant attention recently. However, the cost of communication has become a major challenge for FL as the number of edge devices grows and the complexity of training models increases. Besides, data samples across all edge devices are usually not independent and identically distributed (non-IID), posing additional challenges to the convergence and model accuracy of FL. Therefore, we propose a novel personalized FL framework based on deep coded over-the-air computation, named DipFL. In this framework, we design a deep AirComp aggregation (DACA) module for n-to-1 information aggregation. Besides, a joint source-channel coding (JSCC) module is designed based on the variational auto-encoder (VAE) model, which not only encodes the transmitted data, but also reduces the bias of local samples by introducing certain regularisation terms. In addition, we propose a personalized mix module that allows local models to be more personalized by mixing the global model and the local models. Simulation results confirm that the proposed DipFL framework is able to significantly reduce the amount of transmitted data, while improving FL performance especially at low signal-to-noise regimes.
Sufficient and necessary conditions for reliable lossless communication of two correlated sources over cIasses of phase asynchronous cognitive interference channels are derived. Namely, we consider interference channe...
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ISBN:
(纸本)9781467309219;9781467309202
Sufficient and necessary conditions for reliable lossless communication of two correlated sources over cIasses of phase asynchronous cognitive interference channels are derived. Namely, we consider interference channels in which one of the encoders, i.e., the secondary or cognitive user, is causally or non-causally aware of the other's message. Moreover, as a practical constraint, we assume the transmitters are not aware of the phase shirts introduced by channels. We show that, for both cIasses of causal and noncausal cooperation, under strong interference conditions, separate source and channelcoding is optimal for reliable communication of both users. Also, we derive necessary and sufficient conditions for reliable communication of the cognitive radio transmission while the primary is able to maintain the same information rate it could reliably send in the absence of the secondary. To the best of our knowledge, this is the first work to find fundamental limits of lossless reliable communication for cognitive interference channels.
This paper shows the strong converse and the dispersion of memoryless channels with cost constraints. The analysis is based on a new non-asymptotic converse bound expressed in terms of the distribution of a random var...
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ISBN:
(纸本)9781479904464
This paper shows the strong converse and the dispersion of memoryless channels with cost constraints. The analysis is based on a new non-asymptotic 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 information density in channelcoding without cost constraints. We also analyze the fundamental limits of lossy joint-source-channelcoding over channels with cost constraints.
In the case of high bit rate image transmission or having lots of packets, the FEC (forward error correction) encoding and decoding processes in the ULP (unequal loss protection) based schemes should be applied to ind...
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ISBN:
(纸本)0819455539
In the case of high bit rate image transmission or having lots of packets, the FEC (forward error correction) encoding and decoding processes in the ULP (unequal loss protection) based schemes should be applied to individual packet groups instead of all the packets in order to avoid long processing delay. In this paper, we propose a layered ULP (L-ULP) scheme for fast and efficient FEC allocations among different packet groups and also within each packet group. The numerical results show that the proposed L-ULP scheme is quite promising for fast image transmission over packet loss networks.
We investigate multicast/broadcast of digital video over spread-spectrum CDMA cellular networks, a platform targeted at various kinds of multimedia services. In particular, we propose an end-to-end embedded transmissi...
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ISBN:
(纸本)0819450235
We investigate multicast/broadcast of digital video over spread-spectrum CDMA cellular networks, a platform targeted at various kinds of multimedia services. In particular, we propose an end-to-end embedded transmission scheme which combines a scalable video source coder, adaptive power allocation, adaptive channelcoding and an embedded multiresolution modulation strategy to simultaneously deliver a basic quality-of-service (QoS) to less capable receivers and an enhanced QoS for more capable receivers. We demonstrate the efficacy of this approach using the ITU-T H.263+ video source coder, although the approach is generally applicable to other scalable sourcecoding schemes as well.
We propose a simple, low-complexity coding scheme for the transmission of a packetized progressive bitstream. We consider tandem channels introducing correlated bit errors and packet erasures. We show that our propose...
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ISBN:
(纸本)9781424404810
We propose a simple, low-complexity coding scheme for the transmission of a packetized progressive bitstream. We consider tandem channels introducing correlated bit errors and packet erasures. We show that our proposed technique transforms the hybrid channel into a channel with a single impairment for which various optimization techniques exists. Numerical results show that our proposed scheme outperforms existing solutions over the useful operating regions of the channel.
Lossy transmission of Gaussian sources over energy-limited Gaussian point-to-point and broadcast channels is studied under the infinite bandwidth regime, i.e., when the number of channel uses is unlimited. Using previ...
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Lossy transmission of Gaussian sources over energy-limited Gaussian point-to-point and broadcast channels is studied under the infinite bandwidth regime, i.e., when the number of channel uses is unlimited. Using previously known asymptotic achievability and converse results, the energy-distortion exponent, defined as the rate of decay of the square-error distortion as the available energy-to-noise ratio increases without bound, is completely characterized for both the point-to-point and broadcast channel cases. Turning then to the scenario of zero-delay transmission, where outage events with arbitrarily small probability are allowed, it is shown that the same energy-distortion exponent as in the infinite-delay case can be achieved in all the studied scenarios.
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 present DeepWiVe, the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, com...
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ISBN:
(纸本)9781665494557
We present DeepWiVe, the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channelcoding, and modulation steps into a single neural transform. Our DNN decoder predicts residuals without distortion feedback, which improves video quality by accounting for occlusion/disocclusion and camera movements. We simultaneously train different bandwidth allocation networks for the frames to allow variable bandwidth transmission. Then, we train a bandwidth allocation network using reinforcement learning (RL) that optimizes the allocation of limited available channel bandwidth among video frames to maximize overall visual quality. Our results show that DeepWiVe can overcome the cliffeffect, which is prevalent in conventional separation-based digital communication schemes, and achieve graceful degradation with the mismatch between the estimated and actual channel qualities. DeepWiVe outperforms H.264 video compression followed by lowdensity parity check (LDPC) codes in all channel conditions by up to 0.0485 on average in terms of the multi-scale structural similarity index measure (MS-SSIM).
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