Distributed Wireless Communication in Dense network Environment
Huawei Technologies (March 2016 - ...)
Despite all the advantages of MIMO technology the most part of the existing LTE systems are based on utilizing from 2 to 4 transmit antennas in FDD mode. In order to improve users experience by utilization of many antennas transmission the coordinative
technologies (CBF, JT, JSPC) might be used. However all the coordinative technologies requires fast system information sharing between RRUs which is provided within concepts of C-RAN and IP-RAN. Objectives of this research project are algorithms which allow to improve joint transmission technology and coordinate allocated resources in multi-cell environment.
Despite all the advantages of MIMO technology the most part of the existing LTE systems are based on utilizing from 2 to 4 transmit antennas in FDD mode. In order to improve users experience by utilization of many antennas transmission the coordinative
technologies (CBF, JT, JSPC) might be used. However all the coordinative technologies requires fast system information sharing between RRUs which is provided within concepts of C-RAN and IP-RAN. Objectives of this research project are algorithms which allow to improve joint transmission technology and coordinate allocated resources in multi-cell environment.
MU-MIMO & massive-MIMO
Huawei Technologies (March 2014 - ...)
While the benefits of conventional MIMO systems are well established, it is becoming evident that in the future these systems cannot support the exponentially growing wireless data traffic. Recently, the concept of massive MIMO has been introduced that can significantly improve the performance of wireless networks. In a massive MIMO system, base stations are equipped with arrays comprising of a large number of antennas. As a consequence, the base station with very large array can serve hundreds of users simultaneously. Besides, the effects of small scale fading can be averaged, i.e., the random channel matrix approaches a deterministic matrix. When a number of antennas is asymptotically large, the random channel vectors of individual users become pairwisely orthogonal. It results in the maximization of capacity as the channel matrix becomes now well-conditioned. Another interesting property of massive MIMO is that the simplest forms of user detection and precoding such as matched-filtering and eigenbeamforming are optimal for the case when a number of antennas tends to infinity. With a very large array, the transmit power can be reduced proportionally to a number of antennas used in the array. This is an intriguing feature as the arrays can now be built using a number of tiny and low power antenna devices like radio cube from ALU, it results in the miniaturization of base stations. For these and many other benefits, the massive MIMO technique is now being considered as a promising technology to employ in the next generation wireless networks.
While the benefits of conventional MIMO systems are well established, it is becoming evident that in the future these systems cannot support the exponentially growing wireless data traffic. Recently, the concept of massive MIMO has been introduced that can significantly improve the performance of wireless networks. In a massive MIMO system, base stations are equipped with arrays comprising of a large number of antennas. As a consequence, the base station with very large array can serve hundreds of users simultaneously. Besides, the effects of small scale fading can be averaged, i.e., the random channel matrix approaches a deterministic matrix. When a number of antennas is asymptotically large, the random channel vectors of individual users become pairwisely orthogonal. It results in the maximization of capacity as the channel matrix becomes now well-conditioned. Another interesting property of massive MIMO is that the simplest forms of user detection and precoding such as matched-filtering and eigenbeamforming are optimal for the case when a number of antennas tends to infinity. With a very large array, the transmit power can be reduced proportionally to a number of antennas used in the array. This is an intriguing feature as the arrays can now be built using a number of tiny and low power antenna devices like radio cube from ALU, it results in the miniaturization of base stations. For these and many other benefits, the massive MIMO technique is now being considered as a promising technology to employ in the next generation wireless networks.
Multi-user detection in LTE control channel
Huawei Technologies (August 2011 - May 2014)
New multi-user joint receiver processing for LTE PUCCH that counteracts the intra-cell interference (ICI) is proposed. Using the
fact that the received signal in PUCCH signaling follows a constrained tensor model, a multi-user receiver based on an iterative joint channel/code estimation and symbol detection is proposed. The interest in such a challenging setting relies on the overhead reduction synchronization errors defined by time offset and inaccuracies of timing align. Simulation results show remarkable performance gains of the proposed receiver compared to the conventional time-frequency decorrelator based receiver under the same conditions. DOI: 10.1109/TELFOR.2013.6716250
New multi-user joint receiver processing for LTE PUCCH that counteracts the intra-cell interference (ICI) is proposed. Using the
fact that the received signal in PUCCH signaling follows a constrained tensor model, a multi-user receiver based on an iterative joint channel/code estimation and symbol detection is proposed. The interest in such a challenging setting relies on the overhead reduction synchronization errors defined by time offset and inaccuracies of timing align. Simulation results show remarkable performance gains of the proposed receiver compared to the conventional time-frequency decorrelator based receiver under the same conditions. DOI: 10.1109/TELFOR.2013.6716250
SCADA and wireless network for industrial automation
National Instruments Corporation (February 2011 – August 2011)
Technical Marketing, consulting in control systems and sensor wireless networks:
Technical Marketing, consulting in control systems and sensor wireless networks:
- SCADA systems for industrial automation based on NI PLC and compactRIO platform;
- Smart Grid technologies and wireless sensor networks;
- Computer vision based on NI technologies and LabVIEW.
Virtual University
Southern Federal University (September 2009 - December 2010)
Self-studying materials was developed for remote engineering practice in university laboratories for "Circuit Theory" and "Digital Signal Processing".
Self-studying materials was developed for remote engineering practice in university laboratories for "Circuit Theory" and "Digital Signal Processing".
Reliability Analysis for Early Stage of Design
Southern Federal University (September 2007 - June 2009)
Obviously developers of power systems have no problems with calculation of electric parameters and detection of component parts characteristics. Existing software tools for analysis support this on any stage of design. But the non-failure time forecasting and the estimation of stability of developing products possess some difficulties. There are no established strategies of determination of these parameters on base of circuitry’s and drawings. Such estimations are extremely desirable, particularly at the early stage of design. Firstly it is very expensive to test prototypes (samples of designed product) and secondly it is difficultly realizable process on early stages of designing. It was noted that the intensity of devices failure (the value, inverse mean time of no-failure operation) and intensity of 1/f-noise of those devices are interconnected values. However usage of this fact in design calculations is impossible. Designers have no methods of calculation of intensities of surplus noises with 1/f spectrum without experiments. The technique of noise intensity estimation without experimental data was developed in this project. DOI: 10.1109/TIM.2009.2030911
Obviously developers of power systems have no problems with calculation of electric parameters and detection of component parts characteristics. Existing software tools for analysis support this on any stage of design. But the non-failure time forecasting and the estimation of stability of developing products possess some difficulties. There are no established strategies of determination of these parameters on base of circuitry’s and drawings. Such estimations are extremely desirable, particularly at the early stage of design. Firstly it is very expensive to test prototypes (samples of designed product) and secondly it is difficultly realizable process on early stages of designing. It was noted that the intensity of devices failure (the value, inverse mean time of no-failure operation) and intensity of 1/f-noise of those devices are interconnected values. However usage of this fact in design calculations is impossible. Designers have no methods of calculation of intensities of surplus noises with 1/f spectrum without experiments. The technique of noise intensity estimation without experimental data was developed in this project. DOI: 10.1109/TIM.2009.2030911
High-Dimensional Matrix Computations in EMC problems
Fraunhofer Institute of Algorithms and Scientific Computing (November 2003 - August 2004)
Guest Researcher for electromagnetic compatibility and wave propagation:
Guest Researcher for electromagnetic compatibility and wave propagation:
- Multigrid methods in EMC;
- Gradient Methods in EMC;
- FEEC and PEEC methods for modeling electromagnetic phenomena.
Virtual Test Bed for Power grid and wireless Systems
Taganrog State University of Radio Engineering (March 2000 – December 2006)
The Virtual Test Bed (VTB) comprises a suite of software tools for the prototyping of large-scale, multi-disciplined dynamic systems. It allows proof-testing of new designs prior to hardware construction. The applications driving development of the software primarily relate to advanced power systems such as those for “more electric” implementations of land, air, and sea vehicles, or those for Smart Grid in fixed terrestrial systems. Distinct from the traditional 60 Hz AC power systems, these advanced systems rely heavily on power electronics, point of use energy conversion, distributed energy generation and storage, advanced power sources including fuel cells and gas turbines, and unconventional distribution networks having DC power buses and high numbers of interconnections that can be rapidly reconfigured. These systems cross disciplinary lines so completely that they require a new environment for design, analysis, and specification. The VTB suite of tools strive to fill this need by providing an environment where each team member can fully participate in definition of an interdisciplinary virtual prototype while using their existing intellectual property (component models) and existing modeling skills (preferred languages and environments).
The Virtual Test Bed (VTB) comprises a suite of software tools for the prototyping of large-scale, multi-disciplined dynamic systems. It allows proof-testing of new designs prior to hardware construction. The applications driving development of the software primarily relate to advanced power systems such as those for “more electric” implementations of land, air, and sea vehicles, or those for Smart Grid in fixed terrestrial systems. Distinct from the traditional 60 Hz AC power systems, these advanced systems rely heavily on power electronics, point of use energy conversion, distributed energy generation and storage, advanced power sources including fuel cells and gas turbines, and unconventional distribution networks having DC power buses and high numbers of interconnections that can be rapidly reconfigured. These systems cross disciplinary lines so completely that they require a new environment for design, analysis, and specification. The VTB suite of tools strive to fill this need by providing an environment where each team member can fully participate in definition of an interdisciplinary virtual prototype while using their existing intellectual property (component models) and existing modeling skills (preferred languages and environments).