Abstract—An overview of statistical and information-theoretic aspects of hidden Markov processes (HMPs) is presented. An HMP is a discrete-time finite-state homogeneous Markov chain observed through a discrete-time memoryless invariant channel. In recent years, the work of Baum and Petrie on finite-state finite-alphabet HMPs was expanded to HMPs with finite as well as continuous state spaces and a general alphabet. In particular, statistical properties and ergodic theorems for relative entropy densities of HMPs were developed. Consistency and asymptotic normality of the maximum-likelihood (ML) parameter estimator were proved under some mild conditions. Similar results were established for switching autoregressive processes. These processes generalize HMPs. New algorithms were developed for estimating the state, parameter, and order of an HMP, for universal coding and classification of HMPs, and for universal decoding of hidden Markov channels. These and other related topics are reviewed in this paper. Index Terms—Baum–Petrie algorithm, entropy ergodic theorems, finite-state channels, hidden Markov models, identifiability, Kalman filter, maximum-likelihood (ML) estimation, order estimation, recursive parameter estimation, switching autoregressive processes, Ziv inequality. I.

In many communication situations, the transmitter and the receiver must be designed without a complete knowledge of the probability law governing the channel over which transmission takes place. Various models for such channels and their corresponding capacities are surveyed. Special emphasis is placed on the encoders and decoders which enable reliable communication over these channels.

We consider power and server allocation in a multibeam satellite downlink which transmits data to different ground locations over time-varying channels. Packets destined for each ground location are stored in separate queues and the server rate for each queue depends on the power ( ) allocated to that server and the channel state ( ) according to a concave rate-power curve ( ). We establish the capacity region of all arrival rate vectors ( 1 ... ) which admit a stabilizable system. We then develop a power-allocation policy which stabilizes the system whenever the rate vector lies within the capacity region. Such stability is guaranteed even if the channel model and the specific arrival rates are unknown. Furthermore, the algorithm is shown to be robust to arbitrary variations in the input rates and a bound on average delay is established. As a special case, this analysis verifies stability and provides a performance bound for the Choose-the- -Largest-Connected-Queues policy when channels can be in one of two states (ON or OFF) and servers are allocated at every timestep ( ). These results are extended to treat a joint problem of routing and power allocation in a system with multiple users and satellites and a throughput maximizing algorithm for this joint problem is constructed. Finally, we address the issue of interchannel interference and develop a modified policy when power vectors are constrained to feasible activation sets. Our analysis and problem formulation is also applicable to power control for wireless systems.

Abstract — Hidden Markov models (HMM’s) are a powerful tool for modeling stochastic random processes. They are general enough to model with high accuracy a large variety of processes and are relatively simple allowing us to compute analytically many important parameters of the process which are very difficult to calculate for other models (such as complex Gaussian processes). Another advantage of using HMM’s is the existence of powerful algorithms for fitting them to experimental data and approximating other processes. In this paper, we demonstrate that communication channel fading can be accurately modeled by HMM’s, and we find closed-form solutions for the probability distribution of fade duration and the number of level crossings. Index Terms — Fading channels, hidden Markov models, parameter estimation.

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This paper examines the effectiveness of combining multiple description coding (MDC) and multiple path transport (MPT) for video and image transmission in a multihop mobile radio network. The video and image information is encoded nonhierarchically into multiple descriptions with the following objectives. The received picture quality should be acceptable, even if only one description is received and every additional received description contributes to enhanced picture quality. Typical applications will need a higher bandwidth/higher reliability connection than that provided by a single link in current mobile networks. For supporting these applications, a mobile node may need to set up and use multiple paths to the desired destination, either simply because of the lack of raw bandwidth on a single channel or because of its poor error characteristics, which reduce its effective throughput. In the context of this work, the principal reasons for considering such an architecture are providing high bandwidth and more robust end-to-end connections. We describe a protocol architecture that addresses this need and, with the help of simulations, we demonstrate the feasibility of this system and compare the performance of the MDC-MPT scheme to a system using layered coding and asymmetrical paths for the base and enhancement layers.

Abstract — The quality of wireless links suffers from timevarying channel degradations such as interference, flat-fading, and frequency-selective fading. Current radios are limited in their ability to adapt to these channel variations because they are designed with fixed values for most system parameters such as frame length, error control, and processing gain. The values for these parameters are usually a compromise between the requirements for worst-case channel conditions and the need for low implementation cost. Therefore, in benign channel conditions these commercial radios can consume more battery energy than needed to maintain a desired link quality, while in a severely degraded channel they can consume energy without providing any quality-of-service (QoS). While techniques for adapting radio parameters to channel variations have been studied to improve link performance, in this paper they are applied to minimize battery energy. Specifically, an adaptive radio is being designed that adapts the frame length, error control, processing gain, and equalization to different channel conditions, while minimizing battery energy consumption. Experimental measurements and simulation results are presented in this paper to illustrate the adaptive radio’s energy savings. Index Terms—Adaptive radio, hybrid automatic repeat request (ARQ), maximum likelihood sequence estimation (MLSE), spread spectrum, wireless. I.

Providing quality of service (QoS) guarantees over wireless links requires thorough understanding and quantification of the interactions among the traffic source, the wireless channel, and the underlying link-layer error control mechanisms. In this paper, we account for such interactions in an analytical model that we use to investigate the delay distribution and the packet discard rate over a wireless link. In contrast to previous studies, our analysis accommodates the inherent autocorrelations in both the traffic source as well as the channel error characteristics. An on/off fluid process is used to model the arrival of packets at the transmitter. These packets are temporarily stored in a FIFO buffer before being transmitted over a channel with a time-varying and autocorrelated service rate. Using fluid analysis, we first derive the distribution for the queueing delay at the transmitter. As part of this analysis, we solve a fundamental fluid problem, namely, the probability distribut...

In this paper, we review recent developments concerning the application of lowdensity parity-check (LDPC) codes to the Gilbert-Elliott (GE) channel. Firstly, we discuss the analysis of LDPC estimation-decoding in these channels using density evolution. We show that the required conditions of density evolution are satisfied in the GE channel, and that analysis demonstrates that large potential gains over the memoryless assumption. We also give results which mitigate the complexity of characterizing the GE parameter space using DE. Subsequently, we give a design tool for finding good degree sequences for irregular LDPC codes in the GE channel.

Progressive image transmission is difficult in the presence of a noisy channel, mainly due to the propagation of errors during the decoding of a progressive bitstream. Excellent results for this problem are made possible through combined source-channel coding -- a method that matches the channel code to the source operational rate-distortion as well as channel conditions. This paper focuses on the key component of combined source-channel coding: rate allocation. We develop a parametric methodology for rate allocation in progressive source-channel coding. The key to this technique is an empirical model of decoded bit error rate (BER) as a function of the channel code rate. We investigate several scenarios. In the case of the memoryless channel, we present closed form expressions. For the fading channel and channels with feedback, where closed form results are elusive, our analysis leads to low-complexity algorithms. The results presented in this paper are applicable to any progressive source code, and any family of channel codes.