C.-C.J. Kuo

Cooperative Communications in Resource-Constrained Wireless Networks

Cooperative communications have been proposed to exploit the spatial diversity gains inherent in multiuser wireless systems without the need of multiple antennas at each node. This is achieved by having the users relay each others messages and thus forming multiple transmission paths to the destination. In resource constrained networks, such as wireless sensor networks, the advantages of cooperation can be further exploited by optimally allocating the energy and bandwidth resources among users based on the available channel state information (CSI) at each node. In the first part of this article, we provide a tutorial survey on various power allocation strategies for cooperative networks based on different cooperation strategies, optimizing criteria, and CSI assumptions. In the second part, we identify the similarities between cooperative networks and several sensor network applications that utilize collaboration among distributed sensors to achieve the system goal. These applications include decentralized detection/estimation and data gathering. The techniques developed in cooperative communications can be used to solve many sensor network problems

Environmental Sound Recognition With Time–Frequency Audio Features

The paper considers the task of recognizing environmental sounds for the understanding of a scene or context surrounding an audio sensor. A variety of features have been proposed for audio recognition, including the popular Mel-frequency cepstral coefficients (MFCCs) which describe the audio spectral shape. Environmental sounds, such as chirpings of insects and sounds of rain which are typically noise-like with a broad flat spectrum, may include strong temporal domain signatures. However, only few temporal-domain features have been developed to characterize such diverse audio signals previously. Here, we perform an empirical feature analysis for audio environment characterization and propose to use the matching pursuit (MP) algorithm to obtain effective time-frequency features. The MP-based method utilizes a dictionary of atoms for feature selection, resulting in a flexible, intuitive and physically interpretable set of features. The MP-based feature is adopted to supplement the MFCC features to yield higher recognition accuracy for environmental sounds. Extensive experiments are conducted to demonstrate the effectiveness of these joint features for unstructured environmental sound classification, including listening tests to study human recognition capabilities. Our recognition system has shown to produce comparable performance as human listeners.

Maximum-likelihood synchronization and channel estimation for OFDMA uplink transmissions

Maximum-likelihood estimation of the carrier frequency offset (CFO), timing error, and channel response of each active user in the uplink of an orthogonal frequency-division multiple-access system is investigated in this study, assuming that a training sequence is available. The exact solution to this problem turns out to be too complex for practical purposes as it involves a search over a multidimensional domain. However, making use of the alternating projection method, we replace the above search with a sequence of mono-dimensional searches. This results in an estimation algorithm of a reasonable complexity which is suitable for practical applications. As compared with other existing semi-blind methods, the proposed algorithm requires increased overhead but has more flexibility as it can be used with any subcarrier assignment scheme. Simulations indicate that the accuracy of the CFO estimates asymptotically achieves the Cramer-Rao bound.

Rate Control for H.264 Video With Enhanced Rate and Distortion Models

A new rate control scheme for H.264 video encoding with enhanced rate and distortion models is proposed in this work. Compared with existing H.264 rate control schemes, our scheme has offered several new features. First, the inter-dependency between rate-distortion optimization (RDO) and rate control in H.264 is resolved via quantization parameter estimation and update. Second, since the bits of the header information may occupy a larger portion of the total bit budget, which is especially true when being coded at low bit rates, a rate model for the header information is developed to estimate header bits more accurately. The number of header bits is modeled as a function of the number of nonzero motion vector (MV) elements and the number of MVs. Third, a new source rate model and a distortion model are proposed. For this purpose, coded 4 times 4 blocks are identified and the number of source bits and distortion are modeled as functions of the quantization stepsize and the complexity of coded 4 times 4 blocks. Finally, a R-D optimized bit allocation scheme among macroblocks (MBs) is proposed to improve picture quality. Built upon the above ideas, a rate control algorithm is developed for the H.264 baseline-profile encoder under the constant bit rate constraint. It is shown by experimental results that the new algorithm can control bit rates accurately with the R-D performance significantly better than that of the rate control algorithm implemented in the H.264 software encoder JM8.1a

A Graph Approach to Dynamic Fractional Frequency Reuse (FFR) in Multi-Cell OFDMA Networks

A graph-based framework for dynamic fractional frequency reuse (FFR) in multi-cell OFDMA networks is proposed in this work. FFR is a promising resource allocation technique that can effectively mitigate inter-cell interference (ICI) in OFDMA networks. The proposed scheme enhances the conventional FFR by enabling adaptive spectral sharing per cell load conditions. Such adaptation has significant benefits in a practical environment where traffic load in different cells may be asymmetric and time-varying. The dynamic feature is accomplished via a graph approach in which the resource allocation problem is translated to a graph coloring problem. Specifically, in order to incorporate various versions of FFR in our framework, we construct a graph that matches the specific version of FFR and then color the graph using the corresponding graph algorithm. The performance improvement enabled by the proposed dynamic FFR scheme is further demonstrated by computer simulation for a 19-cell network with asymmetric cell load. For instance, the proposed dynamic FFR scheme can achieve a 12% and 33% gain in cell throughput and service rate over conventional FFR, and render a 70% and 107% gain in cell throughput and service rate with respect to the reuse-3 system.

Hierarchical classification of audio data for archiving and retrieving

A hierarchical system for audio classification and retrieval based on audio content analysis is presented in this paper. The system consists of three stages. The first stage is called the coarse-level audio classification and segmentation, where audio recordings are classified and segmented into speech, music, several types of environmental sounds, and silence, based on morphological and statistical analysis of temporal curves of short-time features of audio signals. In the second stage, environmental sounds are further classified into finer classes such as applause, rain, bird sound, etc. This fine-level classification is based on time-frequency analysis of audio signals and use of the hidden Markov model (HMM) for classification. In the third stage, the query-by-example audio retrieval is implemented where similar sounds can be found according to an input sample audio. It is shown that the proposed system has achieved an accuracy higher than 90% for coarse-level audio classification. Examples of audio fine classification and audio retrieval are also provided.

Multicell OFDMA Downlink Resource Allocation Using a Graphic Framework

A novel practical low-complexity multicell orthogonal frequency-division multiple access (OFDMA) downlink channel-assignment method that uses a graphic framework is proposed in this paper. Our solution consists of two phases: 1) a coarse-scale intercell interference (ICI) management scheme and 2) a fine-scale channel-aware resource-allocation scheme. In the first phase, state-of-the-art ICI management techniques such as ICI coordination (ICIC) and base-station cooperation (BSC) are incorporated in our framework. In particular, the ICI information is acquired through inference from the diversity set of mobile stations and is presented by an interference graph. Then, ICIC or BSC is mapped to the MAX k-CUT problem in graph theory and is solved in the first phase. In the second phase, channel assignment is accomplished by taking instantaneous channel conditions into account. Heuristic algorithms are proposed to efficiently solve both phases of the problem. Extensive simulation is conducted for various practical scenarios to demonstrate the superior performance of the proposed solution compared with the conventional OFDMA allocation scheme. The proposed scheme can be used in next-generation cellular systems such as the 3GPP Long-Term Evolution and IEEE 802.16 m.

Spatial and Temporal Error Concealment Techniques for Video Transmission Over Noisy Channels

Two novel error concealment techniques are proposed for video transmission over noisy channels in this work. First, we present a spatial error concealment method to compensate a lost macroblock in intra-coded frames, in which no useful temporal information is available. Based on selective directional interpolation, our method can recover both smooth and edge areas efficiently. Second, we examine a dynamic mode-weighted error concealment method for replenishing missing pixels in a lost macroblock of inter-coded frames. Our method adopts a decoder-based error tracking model and combines several concealment modes adaptively to minimize the mean square error of each pixel. The method is capable of concealing lost packets as well as reducing the error propagation effect. Extensive simulations have been performed to demonstrate the performance of the proposed methods in error-prone environments

Lifetime maximization for amplify-and-forward cooperative networks

Joint relay-selection and power-allocation strategies are devised to prolong the lifetime of amplify-and-forward (AF) cooperative networks. Lifetime is defined as the time duration within which the desired signal-to-noise ratio (SNR) at the destination is met with a certain probability. Based on selective relaying, we propose three strategies that take into account the local channel state information (CSI) and the local residual energy information (REI) at each relay to prolong the network lifetime. With a finite number of power levels, the energy dissipation process can be modeled as a finite-state Markov chain and the optimal lifetime maximization strategy can be derived using dynamic programming. We demonstrate that the network lifetime can be extended considerably by exploiting both CSI and REI via numerical simulation. The performance of the proposed strategies that utilize only local CSI and REI is shown to be comparable to that of the optimal strategy that demands global CSI and REI.

A cross-Layer quality-of-service mapping architecture for video delivery in wireless networks

Providing quality-of-service (QoS) to video delivery in wireless networks has attracted intensive research over the years. A fundamental problem in this area is how to map QoS criterion at different layers and optimize QoS across the layers. In this paper, we investigate this problem and present a cross-layer mapping architecture for video transmission in wireless networks. There are several important building blocks in this architecture, among others, QoS interaction between video coding and transmission modules, QoS mapping mechanism, video quality adaptation, and source rate constraint derivation. We describe the design and algorithms for each building block, which either builds upon or extend the state-of-the-art algorithms that were developed without much considerations of other layers. Finally, we use simulation results to demonstrate the performance of the proposed architecture for progressive fine granularity scalability video transmission over time-varying and nonstationary wireless channel.