Topics for the MSCSP - Technische Universität Ilmenau · PDF file– Matlab implementation and ... “Performance comparison of space time block codes for ... The millimeter wave

Topics for the MSCSP

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Research ProjectsAdvanced Research Projects

Summer Semester 2017

Selection of topics and submission of topic sheets until

April 20, 2017.

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Department of Electrical Engineering and Information Technology

Institute for Information Technology

Division of Communication Networks

Head: Prof. Dr. rer. nat. habil. Jochen Seitz

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DescriptionVehicle-to-Pedestrian (V2P) communication is necessary to ensure pedestrians' safety. Pedestrians' presence must becommunicated in advance to allow sufficient time for the driver to react irrespectively of varying vehicle/pedestriandensities. The goal of this project is to measure the Time-to-Collision (or vehicle's distance from intersection) for varyingvehicle and pedestrian densities and different periodicity of the pedestrian’s safety message. An urban LOS/NLOSintersection scenario shall be simulated with varying vehicle and pedestrian densities. This scenario shall be used toevaluate impact on Time-to-Collision (TTC).

Tasks Literature survey on V2P communication, medium access schemes and crash scenarios. Design and simulate urban intersection scenarios with different vehicle/pedestrian densities using OMNeT++ & Veins. Implement mechanism to measure TTC. Evaluate the impact of different densities and periodicities on TTC and of different medium access schemes.

References[1] X. Wu, R. Miucic, S. Yang, S. Al-Stouhi, J. Misener, S. Bai, W. Chan. “Cars Talk to Phones: A DSRC Based Vehicle-Pedestrian Safety System”,

80th Vehicular Technology Conference (VTC Fall), 2014.[2] http://www.omnetpp.org

Focus1 student theory / programming / simulation

Impact of Different Vehicle and Pedestrian Densities on Time-to-Collision

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Responsible Professor:Supervisor:

Prof. Jochen SeitzParag Sewalkar

DescriptionIEEE 802.11e is an approved amendment to the IEEE 802.11 standard that defines a set of quality of service (QoS) enhancements for WiFi applications through modifications to the MAC-Layer. The standard is considered of critical importance for delay-sensitive applications, such as Voice over Wireless LAN and streaming multimedia.The goal of this study is to measure the impact of different TXOP settings via Simulations in OMNeT++. TXOP is a specific property of IEEE 802.11e regarding the QoS of voice communication between MANETs. The Evaluation will be based on a in disaster scenario generated by Bonnmotion.

Tasks A literature survey on 802.11e and TXOP and its impact on voice QoS. Design and modelling of typical disaster scenarios using Bonnmotion. Implementation and analysis of TXOP values via suitable simulations in OMNeT++.

References http://www.omnetpp.org & http://sys.cs.uos.de/bonnmotion/ Aschenbruck et al. „Modelling mobility in disaster area scenarios“, 10th ACM Symposium on Modeling,

analysis, and simulation of wireless and mobile systems 2007

Focus1 student theory / programming / measurements / simulations


Prof. Jochen SeitzM. Sc. Silvia Krug & M. Sc. Amine Moussa

Impact of TXOP Variation on Voice Communication Quality in MANETs for Disaster Scenarios

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Lab: Communications Research Laboratory

Head: Prof. Dr.-Ing. Martin Haardt

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Responsible Professor:Research Advisor:E-Mail:

Prof. Martin HaardtM.Sc. Jens [email protected]

• Description:In recent studies, it was shown that parameter estimation methods based on a sparserepresentation of the sensor measurements with an overcomplete basis composed of samplesfrom the array manifold is an effective approach that allows for high resolution capabilities. Thesparsity is enforced by imposing penalties based on the 1-norm. However, the estimation errorscan be further reduced through a weighted regularization, which will be investigated in thisresearch project.

• Tasks: - Understanding the concept of direction of arrival estimation- Study of sparsity-aware processing through regularization- Reproducing the results presented in the given reference

• References:[1] C. Zheng, G. Li, H. Zhang, and X. Wang, “An approach of DOA estimation using noise subspace weightedminization,” in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process, 2011, pp. 2856–2859.

• Focus: 1 student theory & programming

Compressive Sensing Based DOA Estimation

• Description:In EEG data analysis, estimating the number of electromagnetic brain sources is a crucial first step and provides the input parameter for many source localization approaches. The multi-dimensional nature of EEG data gives rise to the interest in exploiting the benefits of tensor-based signal processing for model order estimation using EEG data.

• Tasks– Literature study on model order estimation for EEG data [1] and

tensor-based model order estimation for multi-dimensional harmonic retrieval [2]

– Applying tensor-based model order estimation algorithms on EEG data to estimate the number of sources

– Conducting performance comparison with the existing matrix-based schemes and developing extensions based on the performance evaluation

• References[1] Xiaoxiao Bai and Bin He, “Estimation of Number of Independent Brain Electric Sources from the scalp EEGs,” IEEE Trans. Biomed. Eng., vol. 53, no. 10, pp. 1883 – 1892, Oct. 2006.[2] J. P. C. L. da Costa, F. Roemer, M. Haardt, and R. T. de Sousa Jr., “Multidimensional model order selection,” EURASIP Journal on Advances in Signal Processing, 2011.

• Focus1 student theory / programming / hardware / measurements


Prof. Martin HaardtYao Cheng

Tensor-based Model Order Estimation for EEG Data

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• Description:Tensors provide a useful tool for the analysis of multidimensional data and have very broad range of applications such as compressed sensing, processing of big data, blind source separation and many more. Moreover, tensors and tensor decompositions have been used to describe various communication systems. Within the description of the communication systems arises a new tensor operation, a contraction or a multiproduct. This operations also defines the received signal via wireless channel. Therefore, first we would like to investigate the contraction between two tensors, then we would investigate the tensor rank of different wireless channel models.

• Tasks– Literature study on tensor algebra and tensor decompositions.– Derivation of the contraction operator– Matlab implementation and testing

• References[1] T. G. Kolda and B. W. Bader. “Tensor decompositions and applications”. SIAM, 51:455-500, 2009.[2] M. Haardt, F. Roemer, and G. Del Galdo, ``Higher-order SVD based subspace estimation to improve the parameter

estimation accuracy in multi-dimensional harmonic retrieval problems,'' IEEE Transactions on Signal Processing, vol. 56, pp. 3198-3213, July 2008

Focus 1 student

theory / programming / hardware / measurements


Prof. Martin HaardtKristina Naskovska

Contraction of two tensors and rank estimate of wireless channels

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• Description:5th Generation Non-Orthogonal Waveforms (5GNOW) is an explorative research proposal challenging the obedience of LTE and LTE-Advanced to strict synchronism and orthogonality with respect to future applications. The idea is to abandon synchronism and orthogonality altogether, thereby admitting some crosstalk or interference, and to control these impairments by a suitable transceiver structure and transmission technique. One of the proposed waveforms are Universal Filtered Multicarrier (UFMC) for which we would like to investigate multi user MIMO scenario and propose a tensor model.

• Tasks– Literature study– Derivation and Implementation

• References[1] S. A. Cheema, K. Naskovska, M. Attar, B. Zafar, and M. Haardt. “Performance comparison of space time block codes for

different 5G air interface proposals,'' in Proc. 20-th International ITG Workshop on Smart Antennas (WSA), (Munich, Germany)”. pp. 229 - 235.

[2] V. Stankovic and M. Haardt, ``Multi-user MIMO downlink precoding for users with multiple antennas,'' in Proc. of the 12-th Meeting of the Wireless World Research Forum (WWRF), (Toronto, ON, Canada), Nov. 2004

• Focus

1 student theory / programming / hardware / measurements



Multi User MIMO for UFMC

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• Description:

The NS-IDIEM and IDIEM algorithm is a closed form solution to the simultaneous matrix diagonalization problem. As a first step of this project the existing algorithm should be implemented in Matlab. Then the existing algorithms should be extended to a coupled problem, when two sets of matrices have at least one diagonalizer in common.

• Tasks– Literature study– Derivation and Implementation

• References[1] G. Chabriel and J. Barrere, “A direct algorithm for nonorthogonal approximate joint diagonalization,” IEEE Transactions

on Signal Processing, vol. 60, pp. 39–47, January 2012.

• Focus

1 student theory / programming / hardware / measurements



Implementation of the NS-IDIEM algorithm and extension to the coupled diagonalization problem

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• Description:The SECSI framework calculates an approximation of the CP decomposition based on simultaneous matrix diagonalization. Moreover, the SECSI framework calculates multiple solutions in order to select the best and final solution. The different solutions are independent from one another and therefore the process of their calculation can be paralyzed, resulting in parallel implementation of the framework.

• Tasks– Literature study on tensor algebra and tensor decompositions.– Implementation of the proposed solution

• References[1] T. G. Kolda and B. W. Bader. “Tensor decompositions and applications”. SIAM, 51:455-500, 2009.[2] F. Roemer and M. Haardt, “A semi-algebraic framework for approximate CP decompositions via simultaneous matrix

diagonalizations (SECSI),” Elsevier Signal Processing, vol. 93 , pp. 2722–2738, Sep. 2013

Focus1 student theory / programming / hardware / measurements



Parallel Implementation of the SECSI framework

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• Description:The SECSI framework calculates an approximation of the CP decomposition based on simultaneous matrix diagonalization. Moreover, the SECSI framework calculates multiple solutions in order to select the best and final solution based on different heuristics. For some applications, for instance when calculating the CP decomposition of non-negative tensor better results can be achieved when applying constrained CP decomposition. Therefore, the SECSi framework should be extended to the non-negative SECSI framework.

• Tasks– Literature study on tensor algebra and tensor decompositions.– Implementation of non-negative simulations matrix diagonalization.– Implementation of the non-negative SECSI framework and testing.

• References[1] T. G. Kolda and B. W. Bader. “Tensor decompositions and applications”. SIAM, 51:455-500, 2009.[2] F. Roemer and M. Haardt, “A semi-algebraic framework for approximate CP decompositions via simultaneous matrix

diagonalizations (SECSI),” Elsevier Signal Processing, vol. 93 , pp. 2722–2738, Sep. 2013

Focus1 student theory / programming / hardware / measurements



Non-negative SECSI framework

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Responsible Professor:Research Adviser:E-Mail:

Prof. Dr. -Ing. Martin HaardtDr. -Ing. Jianshu [email protected]

• Description:The millimeter wave massive MIMO channel is often modeled to have only a few scatterers. Thismotivates the use of non-linear estimation methods such as on-grid compressed sensing (CS)algorithms. Nevertheless, the on-grid assumption is impractical. When a frequency-selectivechannel is considered, the multi-dimensional model of the channel estimation problem has not yetbeen exploited.

• Tasks– Literature study of the existing current channel estimation methods– Implement and improve the performance of on-grid CS channel estimation methods, with the

focus oninfluence of practical channel models \ off-grid estimation methods \ multi-dimensional CSchannel estimation methods \ comparison of different CS methods

• References[1] A. Alkhateeb, O. E. Ayach, G. Leus and R. W. Heath, Jr., “Channel estimation and hybrid precoding for millimeter wave cellular

systems", IEEE J. Sel. Topics Signal Process., Oct. 2014.[2] J. Zhang, I. Podkurkov, M. Haardt and A. Nadeev, “Channel estimation and training design for hybrid analog-digital multi-carrier single

user massive MIMO systems”, in Proc. IEEE Int. Workshop on Smart Antennas (WSA), Munich, Germany, Mar. 2016.

Focus1 or 2 students, theory / programming / hardware / measurements / protocols

Channel Estimation Methods for Millimeter Wave Hybrid Massive MIMO Systems

15.08.2013 www.tu- ilmenau.de/ei

_ms_csp

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RF and Microwave Research Laboratory

Head: Prof. Dr. rer. nat. habil. Matthias Hein



Electronic Measurement Research Lab

Head: Prof. Dr.-Ing. habil. Reiner S. Thomä

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Department of Computer Science and Automation

Institute of Computer Engineering

Integrated Communication Systems Group

Head: Prof. Dr.-Ing. habil. Andreas Mitschele-Thiel

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• Description:LORA nodes are low power, long range and low data rate wireless nodes that can be employed for IOT scenarios. The main goal of this project is to develop a testbed for LORA nodes

• Tasks– Assembling IOT nodes using LORA nodes and controllers– Development of a testbed– Measurement of different performance metrics

• Requirements:– Linux– Python, C++– Arduino

• References[1] https://www.lora-alliance.org/

2 student Practical / programming/ hardware


Prof. Andreas Mitschele-ThielMehdi Harounabadi, Victor Casas

Development of a Testbed for LORA Nodes in IoT Scenarios

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• Description:Existing Python-based message ferry simulator evaluates the performance of message ferrying in multi ferry scenarios for stationary nodes. The main goal of this project is to extend the simulator to evaluate the performance of message ferrying for mobile nodes with different mobility models.

• Tasks– Extension of the simulator to evaluate the performance for mobile nodes– Study and investigation of different mobility models for nodes– Modelling the decision maker in ferries

• References[1] Simon, Tobias, and Andreas Mitschele-Thiel. "A self-organized message ferrying algorithm." World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2013 IEEE 14th International Symposium and Workshops on a. IEEE, 2013.

• Focus1 student theory / programming


Prof. Andreas Mitschele-ThielMehdi Harounabadi

Extention of the Python-Based Message Ferry Simulator

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• Description:UAV is a mobility-controlled node can leverage a new degree of freedom in wireless networks which is the trajectory planning for the node. The objective of this project is to implement a new mobility model for wireless nodes which can be controlled by an application in a network simulator. The modelled network will be evaluated under different message forwarding approaches.

• Tasks– Implementing the UAV network in OMNeT++ or NS– Study on the impact of controlling mobility in wireless networks

• References[1] https://omnetpp.org/[2] www.ns.nl/en

Focus2 student theory / programming


Prof. Andreas Mitschele-ThielMehdi Harounabadi

Modeling a UAV Network in a Network Simulator

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https://omnetpp.org/

25.02.2016

www.tu-

ilmenau.de/ei _ms_csp

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Head: Giovanni Del Geldo

Digital Broadcasting Research Laboratory

15.08.2013

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_ms_csp Page 37

Head: Prof. Dr.-Ing. Gerald Schuller

Applied Media Systems

• Description:Active low latency noise reduction approach in terms of unknown noise sources and listener positions is studied. Low latency achieved by implementation signal processing part in a Field-Programmable Gate Array (FPGA). Single board computer PYNQ-Z1 with build-in FPGA module is used.

• Tasks:− State-of-the-art− Novel robust active noise reduction approach implementation− Comparison with State-of-the-art approaches (optional)

• Prerequisites:− Strong audio signal processing knowledge− Strong Python programming skills− Experience in FPGA programming (as an advantage)

• References[1] N. Krishnamurthy, M. Mansour and R. Cole, "Implementation challenges for feedback active noise cancellation," 2012 IEEE International Conference on Acoustics, Speech

and Signal Processing (ICASSP), Kyoto, 2012, pp. 1649-1652. [2] A. J. Efron and L. C. Han, "Wide-area adaptive active noise cancellation," in IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, vol. 41, no.

6, pp. 405-409, Jun 1994.[3] A. V. Oppenheim, E. Weinstein, K. C. Zangi, M. Feder and D. Gauger, "Single-sensor active noise cancellation," in IEEE Transactions on Speech and Audio Processing, vol.

2, no. 2, pp. 285-290, Apr 1994.

• Useful links:Active noise reduction: https://en.wikipedia.org/wiki/Active_noise_controlFPGA: https://en.wikipedia.org/wiki/Field-programmable_gate_arrayPYNQ-Z1 board: http://store.digilentinc.com/pynq-z1-python-productivity-for-zynq/

• Focus:1 student Master Thesis / theory / programming / hardware / measurements


Prof. Dr.-Ing. Gerald SchullerM.Sc. Oleg Golokolenko

Active Low Latency Noise Reduction

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https://en.wikipedia.org/wiki/Active_noise_control

https://en.wikipedia.org/wiki/Field-programmable_gate_array

http://store.digilentinc.com/pynq-z1-python-productivity-for-zynq/


Institute for Media Technology

Electronic Media Technology Labaratory

Head: Prof. Dr.-Ing. Dr. rer. nat. h.c. mult. Karlheinz Brandenburg

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Documents

Topics for the MSCSP - Technische Universität Ilmenau · PDF file– Matlab implementation and ... “Performance comparison of space time block codes for ... The millimeter wave