Papers by Babis Papadopoulos
2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), 2021
In this paper, we develop and evaluate compressed representations of the channels between a massi... more In this paper, we develop and evaluate compressed representations of the channels between a massive MIMO base station and user terminals that can serve as attractive proxies in the context of various applications of interest. To create such compressed channel representations (CCRs), channel features are first extracted from wideband massive-MIMO channel data via appropriate preprocessing in the angular-delay domain. PCA-based and UMAP-based embedding algorithms are then applied to the extracted feature sets to generate the CCR embeddings. We evaluate CCRs in the context of two use cases – user localization and beam tracking – using neural networks. Our ray-tracing based simulation reveals that the proposed CCRs are attractive candidates for these tasks, in terms of not only computation and memory usage but also task performance.
We propose the use of Markov Logic Networks (MLNs) as a highly flexible and expressive formalism ... more We propose the use of Markov Logic Networks (MLNs) as a highly flexible and expressive formalism for the harmonic analysis of audio signals. Using MLNs information about the physical and semantic content of the signal can be intuitively and compactly encoded and expert knowledge can be easily expressed and combined using a single unified formal model that combines probabilities and logic. In particular, we propose a new approach for joint estimation of chord and global key The proposed model is evaluated on a set of popular music songs. The results show that it can achieve similar performance to a state of the art Hidden Markov Model for chord estimation while at the same time estimating global key. In addition when prior information about global key is used it shows a small but statistically significant improvement in chord estimation performance. Our results demonstrate the potential of MLNs for music analysis as they can express both structured relational knowledge as well as uncertainty.
Blind source separation usually obtains limited performance on real and polyphonic music signals.... more Blind source separation usually obtains limited performance on real and polyphonic music signals. To overcome these limitations, it is common to rely on prior knowledge under the form of side information as in Informed Source Separation or on machine learning paradigms applied on a training database. In the context of source separation based on factorization models such as the Non-negative Matrix Factorization, this supervision can be introduced by learning specific dictionaries. However, due to the large diversity of musical signals it is not easy to build sufficiently compact and precise dictionaries that will well characterize the large array of audio sources. In this paper, we argue that it is relevant to construct genrespecific dictionaries. Indeed, we show on a task of harmonic/percussive source separation that the dictionaries built on genre-specific training subsets yield better performances than cross-genre dictionaries.
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221)
We develop algorithms for sequential signal encoding from sensor measurements, and for signal est... more We develop algorithms for sequential signal encoding from sensor measurements, and for signal estimation via fusion of channel-corrupted versions of these encodings. For signals described by state space models, we present optimized sequential binary-valued encodings constructed via thresholdcontrolled scalar quantization of a running Kalman filter signal estimate from the sensor measurements. We also develop methods for robust fusion from observations of these encodings corrupted by binary symmetric channels.
Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181)
Low-complexity schemes for digital encoding of a noise-corrupted signal and associated signal est... more Low-complexity schemes for digital encoding of a noise-corrupted signal and associated signal estimators are presented. This problem arises in wireless distributed sensor networks where an environmental signal of interest is to be estimated at a central site from low-bandwidth digitized information received from collections of remote sensors. We show that the use of a properly designed and often easily implemented additive control input before signal quantization can significantly enhance overall system performance. In particular, efficient estimators can be constructed and used with optimized pseudo-noise, deterministic, and feedbackbased control inputs, resulting in a hierarchy of practical systems with very attractive performance-complexity characteristics.
Dans cet article, nous proposons une methode structuree de decomposition en matrices non-negative... more Dans cet article, nous proposons une methode structuree de decomposition en matrices non-negatives visant a utiliser la structure multi-couche des signaux audio. Les signaux audio peuvent etre vus comme une superposition de deux couches : la couche tonale (modelisee par des sommes de sinuso¨des evoluant lentement en frequence et en temps) et la couche transitoire (les sons percussifs, ´ ev enements de courtes durees etales en frequence). Notre methode decompose une partie du signal en composantes orthogonales parcimonieuses, bien adaptees pour l'extraction tonale tandis que la partie transitoire est representee par des bases de decomposition classiques. Les resultats de separation de sources obtenus sur des signaux reels de musique ont montre que notre approche obtient des resultats similaires a ceux de l'´ etat de l'art. Abstract – In this paper, we propose a new unconstrained nonnegative matrix factorization method designed to utilize the multilayer structure of audio ...
ArXiv, 2018
Cellular networks of massive MIMO base-stations employing TDD/OFDM and relying on uplink training... more Cellular networks of massive MIMO base-stations employing TDD/OFDM and relying on uplink training for both downlink and uplink transmission are viewed as an attractive candidate for 5G deployments, as they promise high area spectral and energy efficiencies with relatively simple low-latency operation. We investigate the use of non-orthogonal uplink pilot designs as a means for improving the area spectral efficiency in the downlink of such massive MIMO cellular networks. We develop a class of pilot designs that are locally orthogonal within each cell, while maintaining low inner-product properties between codes in different cells. Using channel estimates provided by observations on these codes, each cell independently serves its locally active users with MU-MIMO transmission that is also designed to mitigate interference to a subset of `strongly interfered' out-of-cell users. As our simulation-based analysis shows, such cellular operation based on the proposed codes yields user-r...
2018 IEEE International Conference on Communications (ICC), 2018
We propose a novel scheme for estimating the largescale gains of the channels between user termin... more We propose a novel scheme for estimating the largescale gains of the channels between user terminals (UTs) and base stations (BSs) in a cellular system. The scheme leverages TDD operation, uplink (UL) training by means of properly designed non-orthogonal pilot codes, and massive antenna arrays at the BSs. Subject to Q resource elements allocated for UL training and using the new scheme, a BS is able to estimate the large-scale channel gains of K users transmitting UL pilots in its cell and in nearby cells, provided K ď Q 2. Such knowledge of the largescale channel gains of nearby out-of-cells users can be exploited at the BS to mitigate interference to the out-of-cell users that experience the highest levels of interference from the BS. We investigate the large-scale gain estimation performance provided by a variety of non-orthogonal pilot codebook designs. Our simulations suggest that among all the code designs considered, Grassmannian line-packing type codes yield the best large-scale channel gain estimation performance.
2008 IEEE International Conference on Communications, 2008
... provided by an N × K conventional MIMO system (ie, a system relying on K collocated receive a... more ... provided by an N × K conventional MIMO system (ie, a system relying on K collocated receive antennas) [1], [2]. Unlike conventional MIMO, whereby chan-nel state information (CSI) is not required at the transmitter for high spectral efficiency, MU-MIMO systems critically rely on ...
2012 Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2012
2008 46th Annual Allerton Conference on Communication, Control, and Computing, 2008
Abstract We consider a realistic albeit simplified scenario for wireless cellular systems of the ... more Abstract We consider a realistic albeit simplified scenario for wireless cellular systems of the next generation (4G and beyond), where MIMO-OFDM, opportunistic scheduling, channel state information at the transmitter and limited base-station cooperation are envisaged. We propose two strategies with limited base-station cooperation that can be easily implemented with today's technology and achieve an approximate form of inter-cell interference alignment. The first strategy consists of imposing a ldquopower maskrdquo in frequency ...
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013
IEEE GLOBECOM 2007-2007 IEEE Global Telecommunications Conference, 2007
Abstract We present a method for network coding over time-varying networks with attractive trade... more Abstract We present a method for network coding over time-varying networks with attractive tradeoffs between throughput and decoding-delay. We model the time-varying networks as a sequence of topology graphs. The method relies on designing a deterministic network ...
2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011
Recently, Wang etal. [1] proposed MU-MIMO schemes that yield degrees-of-freedom (DoF) gains by en... more Recently, Wang etal. [1] proposed MU-MIMO schemes that yield degrees-of-freedom (DoF) gains by enabling blind interference alignment (BIA), i.e., without requiring channel state information at the transmitter (CSIT). This property allows BIA to avoid many CSIT-related resource and system overheads of conventional CSIT-based MU-MIMO. However, BIA requires terminals to have receive antennas that are able to switch between multiple modes. In this paper we present MU-MIMO schemes that exploit a form of semi-blind interference alignment that does not require multiple antenna modes. The schemes are enabled by opportunistic pairing of users based on features of the users' multipath intensity profiles. This pairing allows suitably remapped versions of the codes in [1] and their extensions to align interference in the frequency domain. The proposed schemes can yield DoF gains with single or multi-antenna terminals, and without requiring antenna-mode switching or transmitter access to fast-changing CSIT. As our representative simulation-based analysis suggests, average DoF gains in the order of 10–25% over SISO (or open loop MIMO) are possible by means of the proposed techniques.
2009 IEEE 70th Vehicular Technology Conference Fall, 2009
In this paper we present reduced-complexity high-performance iterative receivers for single-user ... more In this paper we present reduced-complexity high-performance iterative receivers for single-user MIMO systems that employ OFDM with bit-interleaved coded modulation. The proposed inner-outer decoder structures exploit the Soft-Output M algorithm (SOMA) to calculate bit-likelihood estimates via a limited search on a tree. A key element of the proposed designs is the way the SOMA front-end adapts at each iteration to
2011 IEEE International Conference on Communications (ICC), 2011
Processing Workshop Proceedings, 2004 Sensor Array and Multichannel Signal
In this paper, we develop and evaluate distributed implementations of source localization estimat... more In this paper, we develop and evaluate distributed implementations of source localization estimators from energy-based measurements obtained via an ad-hoc network of acoustic sensors. The distributed locally constructed algorithms that we present produce at each node a sequence of estimates approximating a desired source localization algorithm. As our investigation reveals, the localization performance of these distributed algorithms depends on the
2008 IEEE 68th Vehicular Technology Conference, 2008
In this paper, we propose a near maximum likelihood (ML) scheme for the decoding of multiple inpu... more In this paper, we propose a near maximum likelihood (ML) scheme for the decoding of multiple input multiple output systems. Based on the metric-first search method and by employing Schnorr-Euchner enumeration and branch length thresholds, the proposed scheme provides a higher efficiency than other conventional near ML decoding schemes. From simulation results, it is confirmed that the proposed scheme has lower computational complexity than other near ML decoders while maintaining the bit error rate very close to the ML performance. The proposed scheme in addition possesses the capability of allowing flexible tradeoffs between the computational complexity and BER performance.
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Papers by Babis Papadopoulos