arXiv subjects

Upamanyu Madhow

Publications and source records attributed to Upamanyu Madhow.

45 records · Page 3Linked to original sources

arXiv2015

A scalable architecture for distributed receive beamforming: analysis and experimental demonstration

We propose, analyze and demonstrate an architecture for scalable cooperative reception. In a cluster of N + 1 receive nodes, one node is designated as the final receiver, and the N other nodes act as amplify-and-forward relays which adapt their phases such that the relayed signals add up constructively at the designated receiver. This yields received SNR scaling linearly with N, while avoiding the linear increase in overhead incurred by a direct approach in which received signals are separately quantized and transmitted for centralized processing. By transforming the task of long-distance distributed receive beamforming into one of local distributed transmit beamforming, we can leverage a scalable one-bit feedback algorithm for phase synchronization. We show that time division between the long-distance and local links eliminates the need for explicit frequency synchronization. We provide an analytical framework, whose results closely match Monte Carlo simulations, to evaluate the impact of phase noise due to relaying delay on the performance of the one-bit feedback algorithm. Experimental results from our prototype implementation on software-defined radios demonstrate the expected gains in received signal strength despite significant oscillator drift, and are consistent with results from our analytical framework.

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arXiv2014

Scalable and Efficient Geographic Routing in Mobile Ad Hoc Wireless Networks

We propose and evaluate a scalable position-publish and an accompanying routing protocol which is efficient despite operating with imperfect information regarding the destination's location. The traffic generated by our position-publish protocol fits within the transport capacity of large mobile ad hoc networks (MANETs) with constant communication bandwidth allocated for routing overhead, even as the network size increases. The routing protocol guarantees, with high probability, routes whose lengths are within a constant "stretch" factor of the shortest path from source to destination. The key idea underlying the scalability of the publish protocol is for each potential destination node to send location updates (with frequency decaying with distance) to a subset of network nodes, structured as annular regions around it (the natural approach of updating circular regions in distance-dependent fashion does not scale). The routing protocol must therefore account for the fact that the source and/or relay nodes may not have estimates of the destination's location (or may have stale estimates). Spatial and temporal scaling of protocol parameters are chosen so as to guarantee scalability, route reliability and route stretch, and these analytical design prescriptions are verified using simulations.

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arXiv2014

Compressive parameter estimation in AWGN

Compressed sensing is by now well-established as an effective tool for extracting sparsely distributed information, where sparsity is a discrete concept, referring to the number of dominant nonzero signal components in some basis for the signal space. In this paper, we establish a framework for estimation of continuous-valued parameters based on compressive measurements on a signal corrupted by additive white Gaussian noise (AWGN). While standard compressed sensing based on naive discretization has been shown to suffer from performance loss due to basis mismatch, we demonstrate that this is not an inherent property of compressive measurements. Our contributions are summarized as follows: (a) We identify the isometries required to preserve fundamental estimation-theoretic quantities such as the Ziv-Zakai bound (ZZB) and the Cramer-Rao bound (CRB). Under such isometries, compressive projections can be interpreted simply as a reduction in "effective SNR." (b) We show that the threshold behavior of the ZZB provides a criterion for determining the minimum number of measurements for "accurate" parameter estimation. (c) We provide detailed computations of the number of measurements needed for the isometries in (a) to hold for the problem of frequency estimation in a mixture of sinusoids. We show via simulations that the design criterion in (b) is accurate for estimating the frequency of a single sinusoid.

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arXiv2013

Noncoherent Trellis Coded Quantization: A Practical Limited Feedback Technique for Massive MIMO Systems

Accurate channel state information (CSI) is essential for attaining beamforming gains in single-user (SU) multiple-input multiple-output (MIMO) and multiplexing gains in multi-user (MU) MIMO wireless communication systems. State-of-the-art limited feedback schemes, which rely on pre-defined codebooks for channel quantization, are only appropriate for a small number of transmit antennas and low feedback overhead. In order to scale informed transmitter schemes to emerging massive MIMO systems with a large number of transmit antennas at the base station, one common approach is to employ time division duplexing (TDD) and to exploit the implicit feedback obtained from channel reciprocity. However, most existing cellular deployments are based on frequency division duplexing (FDD), hence it is of great interest to explore backwards compatible massive MIMO upgrades of such systems. For a fixed feedback rate per antenna, the number of codewords for quantizing the channel grows exponentially with the number of antennas, hence generating feedback based on look-up from a standard vector quantized codebook does not scale. In this paper, we propose noncoherent trellis-coded quantization (NTCQ), whose encoding complexity scales linearly with the number of antennas. The approach exploits the duality between source encoding in a Grassmannian manifold and noncoherent sequence detection. Furthermore, since noncoherent detection can be realized near-optimally using a bank of coherent detectors, we obtain a low-complexity implementation of NTCQ encoding using an off-the-shelf Viterbi algorithm applied to standard trellis coded quantization. We also develop advanced NTCQ schemes which utilize various channel properties such as temporal/spatial correlations. Simulation results show the proposed NTCQ and its extensions can achieve near-optimal performance with moderate complexity and feedback overhead.

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arXiv2012

Cooperative localization using angle of arrival measurements: sequential algorithms and non-line-of-sight suppression

We investigate localization of a source based on angle of arrival (AoA) measurements made at a geographically dispersed network of cooperating receivers. The goal is to efficiently compute accurate estimates despite outliers in the AoA measurements due to multipath reflections in non-line-of-sight (NLOS) environments. Maximal likelihood (ML) location estimation in such a setting requires exhaustive testing of estimates from all possible subsets of "good" measurements, which has exponential complexity in the number of measurements. We provide a randomized algorithm that approaches ML performance with linear complexity in the number of measurements. The building block for this algorithm is a low-complexity sequential algorithm for updating the source location estimates under line-of-sight (LOS) environments. Our Bayesian framework can exploit the ability to resolve multiple paths in wideband systems to provide significant performance gains over narrowband systems in NLOS environments, and easily extends to accommodate additional information such as range measurements and prior information about location.

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arXiv2011

Phase-Quantized Block Noncoherent Communication

Analog-to-digital conversion (ADC) is a key bottleneck in scaling DSP-centric receiver architectures to multiGigabit/s speeds. Recent information-theoretic results, obtained under ideal channel conditions (perfect synchronization, no dispersion), indicate that low-precision ADC (1-4 bits) could be a suitable choice for designing such high speed systems. In this work, we study the impact of employing low-precision ADC in a {\it carrier asynchronous} system. Specifically, we consider transmission over the block noncoherent Additive White Gaussian Noise (AWGN) channel, and investigate the achievable performance under low-precision output quantization. We focus attention on an architecture in which the receiver quantizes {\it only the phase} of the received signal: this has the advantage of being implementable without automatic gain control, using multiple 1-bit ADCs preceded by analog multipliers. For standard uniform Phase Shift Keying (PSK) modulation, we study the structure of the transition density of the resulting phase-quantized block noncoherent channel. Several results, based on the symmetry inherent in the channel model, are provided to characterize this transition density. Low-complexity procedures for computing the channel capacity, and for block demodulation, are obtained using these results. Numerical computations are performed to compare the performance of quantized and unquantized systems, for different quantization precisions, and different block lengths. It is observed, for example, that with QPSK modulation, 8-bin phase quantization of the received signal recovers about 80-85% of the capacity attained with unquantized observations, while 12-bin phase quantization recovers more than 90% of the unquantized capacity. Dithering the constellation is shown to improve the performance in the face of drastic quantization.

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arXiv2009

On Block Noncoherent Communication with Low-Precision Phase Quantization at the Receiver

We consider communication over the block noncoherent AWGN channel with low-precision Analog-to-Digital Converters (ADCs) at the receiver. For standard uniform Phase Shift Keying (PSK) modulation, we investigate the performance of a receiver architecture that quantizes only the phase of the received signal; this has the advantage of being implementable without automatic gain control, using multiple 1-bit ADCs preceded by analog multipliers. We study the structure of the transition density of the resulting channel model. Several results, based on the symmetry inherent in the channel, are provided to characterize this transition density. A low complexity procedure for computing the channel capacity is obtained using these results. Numerical capacity computations for QPSK show that 8-bin phase quantization of the received signal recovers more than 80-85 % of the capacity attained with unquantized observations, while 12-bin phase quantization recovers above 90-95 % of the unquantized capacity. Dithering the constellation is shown to improve the performance in the face of drastic quantization.

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arXiv2008

Capacity of the Discrete-Time AWGN Channel Under Output Quantization

We investigate the limits of communication over the discrete-time Additive White Gaussian Noise (AWGN) channel, when the channel output is quantized using a small number of bits. We first provide a proof of our recent conjecture on the optimality of a discrete input distribution in this scenario. Specifically, we show that for any given output quantizer choice with K quantization bins (i.e., a precision of log2 K bits), the input distribution, under an average power constraint, need not have any more than K + 1 mass points to achieve the channel capacity. The cutting-plane algorithm is employed to compute this capacity and to generate optimum input distributions. Numerical optimization over the choice of the quantizer is then performed (for 2-bit and 3-bit symmetric quantization), and the results we obtain show that the loss due to low-precision output quantization, which is small at low signal-to-noise ratio (SNR) as expected, can be quite acceptable even for moderate to high SNR values. For example, at SNRs up to 20 dB, 2-3 bit quantization achieves 80-90% of the capacity achievable using infinite-precision quantization.

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arXiv2008

Transceiver Design with Low-Precision Analog-to-Digital Conversion : An Information-Theoretic Perspective

Modern communication receiver architectures center around digital signal processing (DSP), with the bulk of the receiver processing being performed on digital signals obtained after analog-to-digital conversion (ADC). In this paper, we explore Shannon-theoretic performance limits when ADC precision is drastically reduced, from typical values of 8-12 bits used in current communication transceivers, to 1-3 bits. The goal is to obtain insight on whether DSP-centric transceiver architectures are feasible as communication bandwidths scale up, recognizing that high-precision ADC at high sampling rates is either unavailable, or too costly or power-hungry. Specifically, we evaluate the communication limits imposed by low-precision ADC for the ideal real discrete-time Additive White Gaussian Noise (AWGN) channel, under an average power constraint on the input. For an ADC with K quantization bins (i.e., a precision of log2 K bits), we show that the Shannon capacity is achievable by a discrete input distribution with at most K + 1 mass points. For 2-bin (1-bit) symmetric ADC, this result is tightened to show that binary antipodal signaling is optimum for any signal-to-noise ratio (SNR). For multi-bit ADC, the capacity is computed numerically, and the results obtained are used to make the following encouraging observations regarding system design with low-precision ADC : (a) even at moderately high SNR of up to 20 dB, 2-3 bit quantization results in only 10-20% reduction of spectral efficiency, which is acceptable for large communication bandwidths, (b) standard equiprobable pulse amplitude modulation with ADC thresholds set to implement maximum likelihood hard decisions is asymptotically optimum at high SNR, and works well at low to moderate SNRs as well.

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