Multiple-Description Coding by Dithered Delta-Sigma Quantization

We address the connection between the multiple-description (MD) problem and Delta-Sigma quantization. The inherent redundancy due to oversampling in Delta-Sigma quantization, and the simple linear-additive noise model resulting from dithered lattice quantization, allow us to construct a symmetric and time-invariant MD coding scheme. We show that the use of a noise shaping filter makes it possible to trade off central distortion for side distortion. Asymptotically as the dimension of the lattice vector quantizer and order of the noise shaping filter approach infinity, the entropy rate of the dithered Delta-Sigma quantization scheme approaches the symmetric two-channel MD rate-distortion function for a memoryless Gaussian source and MSE fidelity criterion, at any side-to-central distortion ratio and any resolution. In the optimal scheme, the infinite-order noise shaping filter must be minimum phase and have a piece-wise flat power spectrum with a single jump discontinuity. An important advantage of the proposed design is that it is symmetric in rate and distortion by construction, so the coding rates of the descriptions are identical and there is therefore no need for source splitting.Comment: Revised, restructured, significantly shortened and minor typos has been fixed. Accepted for publication in the IEEE Transactions on Information Theor

Single-amplifier integrator-based low power CMOS filter for video frequency applications

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”This paper describes a new low power fully differential second-order continuous-time low pass filter for use at video frequencies. The filter uses a single active device in combination with MOSFET resistors and grounded capacitors to achieve very low power consumption, small chip area and large dynamic range. The ideal integrator is realised using an internally compensated opamp consisting of only current mirrors and voltage buffers, whilst the lossy integrator is implemented by a single passive RC circuit. The filter has been simulated using a CMOS process. Results show that with a single 5 V power supply, cut-off frequency can be tuned from 3.5 MHz to 8 MHz, dynamic range is better than 67 dB, and power consumption is less than 1.7 mW

Iterative pre-distortion of the non-linear satellite channel

Digital Video Broadcasting - Satellite - Second Generation (DVB-S2) is the current European standard for satellite broadcast and broadband communications. It relies on high order modulations up to 32-amplitude/phase-shift-keying (APSK) in order to increase the system spectral efficiency. Unfortunately, as the modulation order increases, the receiver becomes more sensitive to physical layer impairments, and notably to the distortions induced by the power amplifier and the channelizing filters aboard the satellite. Pre-distortion of the non-linear satellite channel has been studied for many years. However, the performance of existing pre-distortion algorithms generally becomes poor when high-order modulations are used on a non-linear channel with a long memory. In this paper, we investigate a new iterative method that pre-distorts blocks of transmitted symbols so as to minimize the Euclidian distance between the transmitted and received symbols. We also propose approximations to relax the pre-distorter complexity while keeping its performance acceptable

The Infrared Imaging Spectrograph (IRIS) for TMT: Data Reduction System

IRIS (InfraRed Imaging Spectrograph) is the diffraction-limited first light instrument for the Thirty Meter Telescope (TMT) that consists of a near-infrared (0.84 to 2.4 $\mu$m) imager and integral field spectrograph (IFS). The IFS makes use of a lenslet array and slicer for spatial sampling, which will be able to operate in 100's of different modes, including a combination of four plate scales from 4 milliarcseconds (mas) to 50 mas with a large range of filters and gratings. The imager will have a field of view of 34$\times$34 arcsec$^{2}$ with a plate scale of 4 mas with many selectable filters. We present the preliminary design of the data reduction system (DRS) for IRIS that need to address all of these observing modes. Reduction of IRIS data will have unique challenges since it will provide real-time reduction and analysis of the imaging and spectroscopic data during observational sequences, as well as advanced post-processing algorithms. The DRS will support three basic modes of operation of IRIS; reducing data from the imager, the lenslet IFS, and slicer IFS. The DRS will be written in Python, making use of open-source astronomical packages available. In addition to real-time data reduction, the DRS will utilize real-time visualization tools, providing astronomers with up-to-date evaluation of the target acquisition and data quality. The quicklook suite will include visualization tools for 1D, 2D, and 3D raw and reduced images. We discuss the overall requirements of the DRS and visualization tools, as well as necessary calibration data to achieve optimal data quality in order to exploit science cases across all cosmic distance scales.Comment: 13 pages, 2 figures, 6 tables, Proceeding 9913-165 of the SPIE Astronomical Telescopes + Instrumentation 201

Improved Upper Bounds to the Causal Quadratic Rate-Distortion Function for Gaussian Stationary Sources

We improve the existing achievable rate regions for causal and for zero-delay source coding of stationary Gaussian sources under an average mean squared error (MSE) distortion measure. To begin with, we find a closed-form expression for the information-theoretic causal rate-distortion function (RDF) under such distortion measure, denoted by $R_{c}^{it}(D)$, for first-order Gauss-Markov processes. Rc^{it}(D) is a lower bound to the optimal performance theoretically attainable (OPTA) by any causal source code, namely Rc^{op}(D). We show that, for Gaussian sources, the latter can also be upper bounded as Rc^{op}(D)\leq Rc^{it}(D) + 0.5 log_{2}(2\pi e) bits/sample. In order to analyze $R_{c}^{it}(D)$ for arbitrary zero-mean Gaussian stationary sources, we introduce \bar{Rc^{it}}(D), the information-theoretic causal RDF when the reconstruction error is jointly stationary with the source. Based upon \bar{Rc^{it}}(D), we derive three closed-form upper bounds to the additive rate loss defined as \bar{Rc^{it}}(D) - R(D), where R(D) denotes Shannon's RDF. Two of these bounds are strictly smaller than 0.5 bits/sample at all rates. These bounds differ from one another in their tightness and ease of evaluation; the tighter the bound, the more involved its evaluation. We then show that, for any source spectral density and any positive distortion D\leq \sigma_{x}^{2}, \bar{Rc^{it}}(D) can be realized by an AWGN channel surrounded by a unique set of causal pre-, post-, and feedback filters. We show that finding such filters constitutes a convex optimization problem. In order to solve the latter, we propose an iterative optimization procedure that yields the optimal filters and is guaranteed to converge to \bar{Rc^{it}}(D). Finally, by establishing a connection to feedback quantization we design a causal and a zero-delay coding scheme which, for Gaussian sources, achieves...Comment: 47 pages, revised version submitted to IEEE Trans. Information Theor

Massive MIMO with Non-Ideal Arbitrary Arrays: Hardware Scaling Laws and Circuit-Aware Design

Massive multiple-input multiple-output (MIMO) systems are cellular networks where the base stations (BSs) are equipped with unconventionally many antennas, deployed on co-located or distributed arrays. Huge spatial degrees-of-freedom are achieved by coherent processing over these massive arrays, which provide strong signal gains, resilience to imperfect channel knowledge, and low interference. This comes at the price of more infrastructure; the hardware cost and circuit power consumption scale linearly/affinely with the number of BS antennas $N$. Hence, the key to cost-efficient deployment of large arrays is low-cost antenna branches with low circuit power, in contrast to today's conventional expensive and power-hungry BS antenna branches. Such low-cost transceivers are prone to hardware imperfections, but it has been conjectured that the huge degrees-of-freedom would bring robustness to such imperfections. We prove this claim for a generalized uplink system with multiplicative phase-drifts, additive distortion noise, and noise amplification. Specifically, we derive closed-form expressions for the user rates and a scaling law that shows how fast the hardware imperfections can increase with $N$ while maintaining high rates. The connection between this scaling law and the power consumption of different transceiver circuits is rigorously exemplified. This reveals that one can make the circuit power increase as $\sqrt{N}$, instead of linearly, by careful circuit-aware system design.Comment: Accepted for publication in IEEE Transactions on Wireless Communications, 16 pages, 8 figures. The results can be reproduced using the following Matlab code: https://github.com/emilbjornson/hardware-scaling-law

Efficient implementation of filter bank multicarrier systems using circular fast convolution

In this paper, filter bank-based multicarrier systems using a fast convolution approach are investigated. We show that exploiting offset quadrature amplitude modulation enables us to perform FFT/IFFT-based convolution without overlapped processing, and the circular distortion can be discarded as a part of orthogonal interference terms. This property has two advantages. First, it leads to spectral efficiency enhancement in the system by removing the prototype filter transients. Second, the complexity of the system is significantly reduced as the result of using efficient FFT algorithms for convolution. The new scheme is compared with the conventional waveforms in terms of out-of-band radiation, orthogonality, spectral efficiency, and complexity. The performance of the receiver and the equalization methods are investigated and compared with other waveforms through simulations. Moreover, based on the time variant nature of the filter response of the proposed scheme, a pilot-based channel estimation technique with controlled transmit power is developed and analyzed through lower-bound derivations. The proposed transceiver is shown to be a competitive solution for future wireless networks