Projects and Collaborations
Besides our independent research we are involved in several national and international research projects.
In the EXPRESS project we study the compressed sensing (CS) problem in the presence of side information and additional constraints. Side information as well as constraints are due to a specific structure encountered in the system model and may originate from the structure of the measurement system or the sensing matrix (shift-invariance, subarray structure, etc.), the structure of the signal waveforms (integrality, box constraints, constellation constraints such as non-circularity, constant modulus, finite constellation size, etc.), the sparsity structure of the signal (block or group sparsity, rank sparsity, etc.) or the channel, as well as the structure of the measurements (quantization effects, K-bit measures, magnitude-only measurements, etc.). We will investigate in which sense structural information can be incorporated into the CS problem and how it affects existing algorithms and theoretical results. Based on this analysis, we will develop new algorithms and theoretical results particularly suited for these models. It is expected, on the one hand, that exploiting structure in the measurement system, i.e., the sensing matrix, can lead to fast CS algorithms with novel model identifiability conditions and perfect reconstruction/recovery results. In this sense, exploiting structure in the observed signal waveforms and the sparsity structure of the signal representation can lead to reduced complexity CS algorithms with simplified recovery conditions and provably enhanced convergence properties. On the other hand, we expect that quantized measurements, which are of great importance when considering cost efficient hardware and distributed measurement systems, will generally result in a loss of information for which new algorithms and perfect recovery conditions need to be derived.
As an application in this project, we consider collaborative (distributed) multi-dimensional spatial spectrum sensing, i.e., sensing along the frequency-, time-, and space-axes using a network of multi-antenna sensing devices. Depending on the signal model under consideration, the frequency-, time-, and space dependence of the measurements can emerge in several ways. For example, the sensing parameters of interest can include directions-of- arrival, carrier frequencies, and Doppler-shifts. The EXPRESS project aims at exploiting the underlying sparsity properties in the signal model for this application while incorporating the aforementioned various types of side information.
The EXPRESS project is funded by the DFG within the priority program on Compressed Sensing in Information Processing (CoSIP) and is a colaboration of the Communications Research Laboratory, TU Ilmenau, the Communication Systems Group, TU Darmstadt, and the Discrete Optimization Group, TU Darmstadt.
The aim of “Advanced Dynamic spectrum 5G mobile networks Employing Licensed shared access” (ADEL) is to develop future heterogeneous wireless networks of higher capacity and energy efficiency thus setting the road-map for the adoption of spectrum flexible broadband wireless systems by 2020.
The use of spectrum in commercial applications is either licensed or license-exempted. Cognitive radio is another approach but it has been met with skepticism by cellular operators and has led to very limited deployments (e.g. 802.22). ADEL aims at facilitating the reform of spectrum licensing, highly improving the efficiency landscape for personal wireless communications, thus greatly benefiting the citizens. ADEL, while promising a technology breakthrough, also has the advantage of targeting the European spectrum allocation needs and constraints over the years to come.
One main task of our group in ADEL is to develop energy and spectrum efficient collaborative sensing algorithms, where sensing decisions are reached both in a centralized manner (using a central processing unit) and in a fully decentralized manner. In either scheme, the collaborative sensing task shall be carried out under the premise that the total data exchange among the various sensing nodes is kept at a minimum. Towards this aim, we consider the case where in the centralized scheme the measurement data exchanged between the sensing nodes and the central processing unit is aggressively quantized, even to a single bit. In the decentralized scheme we consider a sensing network where sensors only communicate locally with their neighbouring nodes. In this scheme, the objective is to develop distributed algorithms based on the concept of in-network processing, where global sensing information is distributed in the network using consensus propagation techniques, and where global sensing decisions can in the end be carried out autonomously at the individual local nodes.
The ADEL project is a European Research collaborative project, supported by the European Commission, under the CNECT-ICT-619647 grant.
Massive and large-scale MIMO antenna systems are considered to become one of the key enabling technologies in 5G cellular communication networks. The objective of “Benefits And Limitations of large-ScAle MIMO” (BALSAM) is to explore the opportunities and the limitations of large-scale multiuser MIMO downlink transmissions in cellular networks using realistic and computationally efficient system level simulations. For that purpose, a system level architecture is currently being designed that allows a tractable study of large-scale MIMO downlink transmissions from a practical perspective.
Study of the pay-off region for large-scale MIMO is planned, where the regimes, e.g. antenna configurations, number of simultaneously served users, etc., will be determined in order to identify under which conditions the implementation of large-scale MIMO shows a clear benefit over conventional MIMO with a limited increase of complexity. Additionally, the analysis of massive MIMO performance under realistic channel conditions with hardware artifacts and channel state mismatch will be performed. For that purpose, modeling of hardware impairments, channel state information mismatch and residual interference, among others will take place.
The BALSAM project is funded by Telekom Innovation Laboratories (T-Labs) and is a collaboration of the Wireless Technologies & Networks team, T-Labs, and the Communication Systems Group, TU Darmstadt.