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Reproducible Research

The Division of Information Science and Engineering is committed to reproducible research. On this page, we provide links to software frameworks developed by the division, as well as source code to the simulation environment for select publications.

Software frameworks

Greedy sparse learning over network

Please find the reproducible code here (zip 17 kB)

Generalized Fusion Algorithm for Compressive Sampling Reconstruction and RIP-based Analysis

Please find the reproducible code here (zip 22 kB)

ARK (Bioinformatics - Bacterial Community Composition)

ARK - Aggregation of Reads by K-means for Bacterial Community Composition. Please download the reproducible code from here ARK (zip 3.5 MB)

Distributed Greedy Pursuit Algorithms (Compressed Sensing)

Check the readme file (zip 120 kB)

DIPP - Distributed Parallel Pursuit (Compressed Sensing)

DIPP - Distributed Parallel Pursuit.zip (zip 169 kB)

The figures are generated under ./data/ folder. The data is generated from the files in ./ folder. The algorithms are in the ./algorithms/ folder.

SEK (Bioinformatics - bacterial community composition)

The software uses Matlab environment. It provides one click approach to reproduce Fig. 2 of the paper "SEK: Sparsity exploiting k-mer-based estimation of bacterial community composition". The software includes a README file where detailed description is given.

Download here (zip 3.5 MB)

four_multi

Four-multi is a software framework targeted towards testbed implementations of wireless systems involving multiple antennas (per node), multiple-nodes (in the system and/or per cells), multiple-band (e.g several spectrum segments), and multiple cells. Four-multi runs on a special configuration of USRPs (see "requirements" below). Four-multi is packaged in a library (libfour_multi). Four-multi is released under the terms of the GNU General Public License (GPL).

OpenShoe

Open­Shoe is an aca­d­e­mic project for cre­at­ing an open source embed­ded foot-mounted INS imple­men­ta­tion. The project con­tain both hard­ware and soft­ware com­po­nents all of which are doc­u­mented and released under open source licenses.

CoordinatedPrecoding.jl

CoordinatedPrecoding.jl is a Julia  package for the simulation of wireless networks, in particular multicell multiple-input multiple-output (MIMO) networks operating using coordinated precoding.

Measurements

TDD reciprocity measurement

A few channel measurements to test channel reciprocity. Check README.txt for documentation.

Source code from publications

Authors Title Appears in Source Code
S. Chatterjee, A. M. Javid, M. Sadeghi, S Kikuta, P. P. Mitra, M. Skoglund SSFN: Self Size-estimating Feed-forward Network and Low Complexity Design   Self Size-estimating Feed-forward Network (SSFN).zip (zip 1.6 MB)
A. Venkitaraman, S. Chatterjee, and P. Händel Kernel regression for signals over graphs   kergraphcodes.zip (zip 7.2 MB)
A. Zaki, P. P. Mitra, L. K. Rasmussen and S. Chatterjee Estimate Exchange over Network is Good for Distributed Hard Thresholding Pursuit Signal Processing, 156, 1-11. DHTP_code.zip (zip 17 kB)
A. Venkitaraman, S. Chatterjee, and P. Händel Hilbert Transform, Analytic Signal, and Modulation Analysis for Graph Signal Processing Submitted to Elsevier Signal Processing Journal Matlab code (zip 120 kB)
R. Brandt, R. Mochaourab, and M. Bengtsson Globally Optimal Base Station Clustering in Interference Alignment-Based Multicell Networks IEEE Signal Processing Letters 23.4 (2016): 512-516. GitHub
R. Brandt, R. Mochaourab, and M. Bengtsson Interference Alignment-Aided Base Station Clustering using Coalition Formation Proceedings of the 49th Asilomar Conf. on Signals, Systems, Computers, 2015. GitHub
R. Brandt and M. Bengtsson Fast-Convergent Distributed Coordinated Precoding for TDD Multicell MIMO Systems Proceedings of IEEE Int. Workshop Computational Advances in Multi-Sensor Adaptive Process. (CAMSAP'15) GitHub
E. Zenteno, R. Piazza, M. R. Bhavani Shankar, D. Rönnow, and B. Ottersten

A MIMO symbol rate signal digital predistorter for nonlinear multicarrier satellite channels

IET Communications, to be published 2015. 

Demo tool (pdf) (pdf 68 kB)

E. Zenteno, R. Piazza, M. R. Bhavani Shankar, D. Rönnow, and B. Ottersten

Low complexity predistortion and equalization in nonlinear multicarrier satellite communications

EURASIP J. on Advances in Signal Processing, vol. 2015, no. 1, p. 30, 2015. 

See demo tool above.
R. Brandt, M. Bengtsson Distributed CSI Acquisition and Coordinated Precoding for TDD Multicell MIMO Systems IEEE Transactions on Vehicular Technology, in press Matlab code

Z.Khan, E. Zenteno, M. Isaksson, P. Händel

Density Estimation Models for Strong Nonlinearities in RF Power Amplifiers

Proceedings of Asia Pacific Microwave Conference, Sendai, Japan, Nov. 2014

Matlab code (zip 7 kB) Measurement data (30 MB)
E. Björnson, M. Bengtsson, B. Ottersten

Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure

IEEE Signal Processing Magazine, vol. 31, no. 4, pp. 142-148, July 2014

Matlab code
R. Brandt, E. Björnson, M. Bengtsson Weighted Sum Rate Optimization for Multicell MIMO Systems with Hardware-Impaired Transceivers

Proceedings of IEEE Conference on Acoustics, Speech, and Signal Processing (ICASSP), Florence, Italy, May 2014

Matlab code
D. Zachariah, A. de Angelis, S. Dwivedi, P. Händel Schedule based sequential localization in asynchronous wireless networks

EURASIP Journal on Advances in Signal Processing, February 2014

Download (zip 11 kB)
E. Björnson, M. Matthaiou, M. Debbah

A New Look at Dual-Hop Relaying: Performance Limits with Hardware Impairments

IEEE Transactions on Communications, vol. 61, no. 11, pp. 4512-4525, November 2013

Matlab code
E. Björnson, M. Kountouris, M. Bengtsson, B. Ottersten

Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users

IEEE Transactions on Signal Processing, vol. 61, no. 13, pp. 3431-3446, July 2013

Matlab code
M. Matthaiou, A. Papadogiannis, E. Björnson, M. Debbah

Two-way Relaying under the Presence of Relay Transceiver Hardware Impairments

IEEE Communications Letters, vol. 17, no. 6, pp. 1136-1139, June 2013

Matlab code
E. Björnson, A. Papadogiannis, M. Matthaiou, M. Debbah

On the impact of transceiver impairments on AF relaying

Proceedings of IEEE Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vancouver, Canada, May 2013

Matlab code
E. Björnson, P. Zetterberg, M. Bengtsson, B. Ottersten

Capacity Limits and Multiplexing Gains of MIMO Channels with Transceiver Impairments

IEEE Communications Letters, vol. 17, no. 1, pp. 91-94, January 2013

Matlab code
E. Björnson, E. Jorswick

Optimal Resource Allocation in Coordinated Multi-Cell Systems

Foundations and Trends in Communications and Information Theory, vol. 9, no. 2-3, pp. 113-381, 2013

Matlab code
P. Zetterberg, N. M. Moghadam An Experimental Investigation of SIMO, MIMO, Interference-Alignment (IA) and Coordinated Multi-Point (CoMP)

Proceedings of Int. Conf. Systems, Signals, Image Process. (IWSSIP), Vienna, Austria, 2012

SourceForge
E. Björnson, B. Ottersten

A Framework for Training-Based Estimation in Arbitrarily Correlated Rician MIMO Channels with Rician Disturbance

IEEE Transactions on Signal Processing, vol. 58, no. 3, pp. 1807-1820, March 2010

Matlab code
M.Sundin, C.R. Rojas, M. Jansson and S.Chatterjee  Relevance Singular Vector Machine for Low-rank Matrix Reconstruction​ IEEE Transaction on Signal Processing, 2015. Submitted. GitHub
Page responsible:Mats Bengtsson
Belongs to: Information Science and Engineering
Last changed: Jan 29, 2020