An adaptive and integrated video communication system is proposed for wireless ATM. Video received from the wireline source is adapted at the base station to both the hardware capabilities of mobile host and time-vary...
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An adaptive and integrated video communication system is proposed for wireless ATM. Video received from the wireline source is adapted at the base station to both the hardware capabilities of mobile host and time-varying wireless channel conditions. Following the application level framing principle, source coding, channel coding, and packetization are jointly implemented as part of the application and only simple services are requested from the underlying wireless network infrastructure. Highly efficient and robust source coding, channel coding, and packetization techniques are also proposed. For source coding, we propose to use our three-dimensional significance-linked connected component analysis video codec. For channel coding and packetization, both intracell and interlaced (intercell) forward error correction are applied. Furthermore, the time-varying channel characteristics is exploited by adaptively allocating the total bit budget between source coding and channel coding. Performance evaluation demonstrates the effectiveness of the proposed wireless video communication system.
This article presents a new procedure for the recovery of a signal from its nonuniform samples based on the root distribution of a given function; as an example, an orthonormal sampling expansion analogue to the Shann...
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This article presents a new procedure for the recovery of a signal from its nonuniform samples based on the root distribution of a given function; as an example, an orthonormal sampling expansion analogue to the Shannon expansion is shown to be useful in the recovery. We also extend the concept of a "bandlimited signal" to transformed domains other than the Fourier domain.< >
Proposes a new model for characterizing the data traffic in a multi-media environment. The authors model the data traffic by a two-state doubly stochastic Poisson process, with sojourn times in each state having an in...
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Proposes a new model for characterizing the data traffic in a multi-media environment. The authors model the data traffic by a two-state doubly stochastic Poisson process, with sojourn times in each state having an independent and identical heavy tailed distribution, such as the Pareto distribution. The simulation results from the new data traffic model are presented. The new model is versatile in capturing the self-similar characteristics of traffic found in the traffic measurements. The authors also suggest that the other two types of multi-media traffic namely, voice and video may each be characterized by a 2-state doubly stochastic Poisson process with exponential sojourn times (i.e., a Markov modulated Poisson process or MMPP).
Orthogonal frequency division multiplexing (OFDM) can be used with a multiple-input multiple-output (MIMO) system to improve communication quality and capacity. Pilot-symbol-aided or decision-directed channel estimati...
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Orthogonal frequency division multiplexing (OFDM) can be used with a multiple-input multiple-output (MIMO) system to improve communication quality and capacity. Pilot-symbol-aided or decision-directed channel estimation must be used to track channel variations in MIMO-OFDM systems. While pilot symbols facilitate channel estimation, they reduce the transmit energy for data symbols under a fixed total transmit power constraint. We analyze the effects of pilot-symbol-aided channel estimation on the lower bound of the capacity and derive the optimal pilot-to-data power ratio (PDPR) in MIMO-OFDM systems with three different types of pilot patterns: independent, scattered, and orthogonal. The result implies that implementing the optimal PDPR in an actual MIMO-OFDM system should prove relatively straightforward, since there is a surprisingly broad range of PDPR values over which near optimal capacity is achieved.
In this paper, we propose a new decoding algorithm for quasiorthogonal space-time block codes (QOSTBCs) which achieves near maximum likelihood (ML) performance while substantially reducing the decoding complexity. We ...
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In this paper, we propose a new decoding algorithm for quasiorthogonal space-time block codes (QOSTBCs) which achieves near maximum likelihood (ML) performance while substantially reducing the decoding complexity. We show that for a system with rate r = n s /T, where n s is the number of transmitted symbols per T time slots; the proposed algorithm decomposes the original complex-valued system into a parallel system with n s 2times2 real-valued components, thus allowing for a simple decoding of one real symbol at a time. For a square QAM constellation with L points (L-QAM), this algorithm achieves full diversity by properly incorporating two-dimensional rotation using the optimal rotation angle and the same rotating matrix for any number of transmit antennas (Nges4). We show that the complexity of this algorithm is linear with the number of transmitted symbols n s , and is independent of the constellation size L.
A new approach for the identification of minimum-phase autoregressive moving average (ARMA) systems in the presence of heavy noise is presented in this paper. A damped sinusoidal (DS) model for the autocorrelation fun...
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A new approach for the identification of minimum-phase autoregressive moving average (ARMA) systems in the presence of heavy noise is presented in this paper. A damped sinusoidal (DS) model for the autocorrelation function of a noise-free ARMA signal is proposed to estimate the AR parameters, which overcomes the failure of conventional correlation based techniques in estimating the AR parameters of an ARMA system at a very low signal-to-noise ratio (SNR). The MA parameters of the ARMA system are then estimated by using Durbin's method along with an optimum order selection criterion. Both white noise and periodic impulse train excitations are considered for the application of the proposed method to system identification as well as to speech processing. computer simulations are carried out based on both synthetic ARMA systems and natural speech signals, showing superior identification results even at an SNR of -5 dB for which most of the existing methods would fail.
Multimedia systems are often divided into presentational and conversational domains: those which orchestrate prerecorded scenarios and those which provide audio/video teleconferencing. To be effective across a wide ra...
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Multimedia systems are often divided into presentational and conversational domains: those which orchestrate prerecorded scenarios and those which provide audio/video teleconferencing. To be effective across a wide range of activities, however, collaborative multimedia systems must support the integration of presentational, conversational and interactive multimedia within a single shared media space. Such a virtual environment must not only support synthetic and real-time media but also their interactive manipulation as shared objects. Therefore, synchronizing media and the actions upon them in both a timely and causal manner are necessary to maintain a semantically coherent workspace. This paper discusses these issues and introduces a framework based on Virtual Enablers and Virtual Barriers designed to support the diverse range of synchronization requirements within collaborative multimedia systems. Its associated architecture is described and the model's application to the field of telelearning is illustrated.
The paper presents a new approach for the identification of minimum-phase autoregressive (AR) systems in the presence of heavy noise. A damped cosine model for the ramp cepstrum of the one-sided autocorrelation functi...
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The paper presents a new approach for the identification of minimum-phase autoregressive (AR) systems in the presence of heavy noise. A damped cosine model for the ramp cepstrum of the one-sided autocorrelation function of a noise-free AR signal is proposed to estimate the AR parameters. The AR parameters are obtained directly from the estimated damped cosine model parameters. The proposed method overcomes the failure of conventional cepstrum and correlation based techniques in noisy AR system identification at a very low signal-to-noise ratio (SNR). computer simulations are carried out based on. both synthetic AR systems and natural speech signals, showing superior identification results even at an SNR of -5 dB for which most of the existing methods would fail.
This paper investigates orthogonal space-time block coded transmission for a multiple-input multiple-output (MIMO) channel with non-coherent amplify-and-forward relaying in a situation where the source-relay and relay...
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This paper addresses the problem of multi-program video transmission over a single communication channel. We present a joint bit-allocation for MPEG encoding of multiple video sequences with a minimum quality-variatio...
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This paper addresses the problem of multi-program video transmission over a single communication channel. We present a joint bit-allocation for MPEG encoding of multiple video sequences with a minimum quality-variation. The proposed method uses a picture-complexity measure based on the actual coding distortion in encoded frames, then allocates accordingly the available bits to explicitly reduce the variation in quality between the sequences. We compare the performance of the proposed method to independent encoding of the sequences at constant bit rates and to encoding with a joint bit-allocation scheme that uses a TM5-like picture-complexity measure. Results show that the proposed bit-allocation method is superior in terms of minimizing the quality variation between the video sequences and within the individual sequences. The method also provides better minimum picture quality than the other encoding schemes mentioned above. Applications of the joint bit-allocation method include multi-program transmission such as video on demand (VOD) services and digital TV broadcasting.
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