2,496 research outputs found
Modeling of Orthogonal Frequency Division Multiplexing (OFDM) for Transmission in Broadband Wireless Communications
Orthogonal Frequency Division Multiplexing (OFDM) is a multi carrier modulation technique that provides high bandwidth efficiency because the carriers are orthogonal to each other and multiple carriers share the data among themselves. The main advantage of this transmission technique is its robustness to channel fading in wireless communication environment. This paper investigates the effectiveness of OFDM and assesses its suitability as a modulation technique in wireless communications. Several of the main factors affecting the performance of a typical OFDM system are considered and they include multipath delay spread, channel noise, distortion (clipping), and timing requirements. The core processing block and performance analysis of the system is modeled usingMatlab
Near-Instantaneously Adaptive HSDPA-Style OFDM Versus MC-CDMA Transceivers for WIFI, WIMAX, and Next-Generation Cellular Systems
Burts-by-burst (BbB) adaptive high-speed downlink packet access (HSDPA) style multicarrier systems are reviewed, identifying their most critical design aspects. These systems exhibit numerous attractive features, rendering them eminently eligible for employment in next-generation wireless systems. It is argued that BbB-adaptive or symbol-by-symbol adaptive orthogonal frequency division multiplex (OFDM) modems counteract the near instantaneous channel quality variations and hence attain an increased throughput or robustness in comparison to their fixed-mode counterparts. Although they act quite differently, various diversity techniques, such as Rake receivers and space-time block coding (STBC) are also capable of mitigating the channel quality variations in their effort to reduce the bit error ratio (BER), provided that the individual antenna elements experience independent fading. By contrast, in the presence of correlated fading imposed by shadowing or time-variant multiuser interference, the benefits of space-time coding erode and it is unrealistic to expect that a fixed-mode space-time coded system remains capable of maintaining a near-constant BER
Radio Astronomy
Contains table of contents and reports on seven research projects.National Science Foundation (Grant AST 86-17172)National Aeronautics and Space AdministrationJet Propulsion LaboratoryNASA/Goddard Space Flight Center (Grant NAG5-10)SM Systems and Research, Inc.U.S. Navy Office of Naval Research (Contract N00014-86-C-2114)Center for Advanced Television StudiesNASA/Goddard Space Flight Center (Grant NAG5-537
Reconsidering Linear Transmit Signal Processing in 1-Bit Quantized Multi-User MISO Systems
In this contribution, we investigate a coarsely quantized Multi-User
(MU)-Multiple Input Single Output (MISO) downlink communication system, where
we assume 1-Bit Digital-to-Analog Converters (DACs) at the Base Station (BS)
antennas. First, we analyze the achievable sum rate lower-bound using the
Bussgang decomposition. In the presence of the non-linear quanization, our
analysis indicates the potential merit of reconsidering traditional signal
processing techniques in coarsely quantized systems, i.e., reconsidering
transmit covariance matrices whose rank is equal to the rank of the channel.
Furthermore, in the second part of this paper, we propose a linear precoder
design which achieves the predicted increase in performance compared with a
state of the art linear precoder design. Moreover, our linear signal processing
algorithm allows for higher-order modulation schemes to be employed
Multiple Description Quantization via Gram-Schmidt Orthogonalization
The multiple description (MD) problem has received considerable attention as
a model of information transmission over unreliable channels. A general
framework for designing efficient multiple description quantization schemes is
proposed in this paper. We provide a systematic treatment of the El Gamal-Cover
(EGC) achievable MD rate-distortion region, and show that any point in the EGC
region can be achieved via a successive quantization scheme along with
quantization splitting. For the quadratic Gaussian case, the proposed scheme
has an intrinsic connection with the Gram-Schmidt orthogonalization, which
implies that the whole Gaussian MD rate-distortion region is achievable with a
sequential dithered lattice-based quantization scheme as the dimension of the
(optimal) lattice quantizers becomes large. Moreover, this scheme is shown to
be universal for all i.i.d. smooth sources with performance no worse than that
for an i.i.d. Gaussian source with the same variance and asymptotically optimal
at high resolution. A class of low-complexity MD scalar quantizers in the
proposed general framework also is constructed and is illustrated
geometrically; the performance is analyzed in the high resolution regime, which
exhibits a noticeable improvement over the existing MD scalar quantization
schemes.Comment: 48 pages; submitted to IEEE Transactions on Information Theor
Performance and Complexity Co-Evaluations of MPEG4-ALS Compression Standard for Low-Latency Music Compression
In this thesis compression ratio and latency of different classical audio music tracks are analyzed with various encoder options of MPEG4ALS. Different tracks of audio music tracks are tested with MPEG4-ALS coder with different options to find the optimum values for various parameters to obtain maximum compression ratio with minimum CPU time (encoder and decoder time). Optimum frame length for which the compression ratio saturates for music audio is found out by analyzing the results when different classical music tracks are experimented with various frame lengths. Also music tracks with varying sampling rate are tested and the compression ratio and latency relationship with sampling rate are analyzed and plotted. It is found that the compression gain rate was higher when the codec complexity is less, and joint channel correlation and long term correlations are not significant and latency trade off make the more complex codec options unsuitable for applications where latency is critical. When the two entropy coding options, Rice code and BGMC (Block Gilbert-Moore Codes) are applied on various classical music tracks, it was obvious that the Rice code is more suitable for low-latency applications compared to the more complex BGMC coding, as BGMC improved compression performance with the expense of latency, making it unsuitable in real-time applications
Sparsity and morphological diversity for multivalued data analysis
International audienceThe recent development of multi-channel sensors has motivated interest in devising new methods for the coherent processing of multivariate data. An extensive work has already been dedicated to multivariate data processing ranging from blind source separation (BSS) to multi/hyper-spectral data restoration. Previous work1 has emphasized on the fundamental role played by sparsity and morphological diversity to enhance multichannel signal processing. GMCA is a recent algorithm for multichannel data analysis which was used successfully in a variety of applications including multichannel sparse decomposition, blind source separation (BSS), color image restoration and inpainting. Inspired by GMCA, a recently introduced algorithm coined HypGMCA is described for BSS applications in hyperspectral data processing. It assumes the collected data is a linear instantaneous mixture of components exhibiting sparse spectral signatures as well as sparse spatial morphologies, each in specified dictionaries of spectral and spatial waveforms. We report on numerical experiments with synthetic data and application to real observations which demonstrate the validity of the proposed method
Compensation of Laser Phase Noise Using DSP in Multichannel Fiber-Optic Communications
One of the main impairments that limit the throughput of fiber-optic communication systems is laser phase noise, where the phase of the laser output drifts with time. This impairment can be highly correlated across channels that share lasers in multichannel fiber-optic systems based on, e.g., wavelength-division multiplexing using frequency combs or space-division multiplexing. In this thesis, potential improvements in the system tolerance to laser phase noise that are obtained through the use of joint-channel digital signal processing are investigated. To accomplish this, a simple multichannel phase-noise model is proposed, in which the phase noise is arbitrarily correlated across the channels. Using this model, high-performance pilot-aided phase-noise compensation and data-detection algorithms are designed for multichannel fiber-optic systems using Bayesian-inference frameworks. Through Monte Carlo simulations of coded transmission in the presence of moderate laser phase noise, it is shown that joint-channel processing can yield close to a 1 dB improvement in power efficiency. It is further shown that the algorithms are highly dependent on the positions of pilots across time and channels. Hence, the problem of identifying effective pilot distributions is studied.The proposed phase-noise model and algorithms are validated using experimental data based on uncoded space-division multiplexed transmission through a weakly-coupled, homogeneous, single-mode, 3-core fiber. It is found that the performance improvements predicted by simulations based on the model are reasonably close to the experimental results. Moreover, joint-channel processing is found to increase the maximum tolerable transmission distance by up to 10% for practical pilot rates.Various phenomena decorrelate the laser phase noise between channels in multichannel transmission, reducing the potency of schemes that exploit this correlation. One such phenomenon is intercore skew, where the spatial channels experience different propagation velocities. The effect of intercore skew on the performance of joint-core phase-noise compensation is studied. Assuming that the channels are aligned in the receiver, joint-core processing is found to be beneficial in the presence of skew if the linewidth of the local oscillator is lower than the light-source laser linewidth.In the case that the laser phase noise is completely uncorrelated across channels in multichannel transmission, it is shown that the system performance can be improved by applying transmitter-side multidimensional signal rotations. This is found by numerically optimizing rotations of four-dimensional signals that are transmitted through two channels. Structured four-dimensional rotations based on Hadamard matrices are found to be near-optimal. Moreover, in the case of high signal-to-noise ratios and high signal dimensionalities, Hadamard-based rotations are found to increase the achievable information rate by up to 0.25 bits per complex symbol for transmission of higher-order modulations
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