Network MIMO and Relaying

 

 

Network MIMO and relaying systems have recently attracted a lot of interest in the research community because of their potential benefits for the next generation of wireless networks. Modern and future cellular networks often rely on an aggressive frequency reuse, which increases the capacity but also generates higher levels of interest especially near the cell borders. Network MIMO and relaying schemes have the ability to offer a substantial increase in data rates and to mitigate interference more effectively due to the degrees of freedom offered by the increase degrees of freedom.

 

Network MIMO systems are motivated by the need to employ smaller cells to increase the capacity, resulting in increased levels of interference near the cell edges. By connecting the distributed base stations with high-capacity wired or wireless backhaul, channel state information and data received by each base station can be shared in a MIMO network, and a powerful large-scale MIMO cooperation scheme can be realized.  Key problems in such systems include the need for considerable signalling and high-capacity wired or wireless backhauls, resource allocation, cost-effective precoding and detection algorithms and novel network architectures and concepts.

Base station cooperating to perform joint multiuser detection, where each cluster has 4 BS and 4 users.

 

In our 5G lab, we look at innovative solutions to the problems encountered in the design of these systems, namely:

o   Precoding and detection

o   Strategies to reduce signalling and use of backhaul

o   Resource allocation

o   Distributed architectures

 

Selected Publications:

 

P. Li and R. C. de Lamare, "Distributed Iterative Detection with Reduced Message Passing for Networked MIMO Cellular Systems", IEEE Transactions on Vehicular Technology, 2014. pdf

 

B. Song, F. Roemer, and M. Haardt, ``Flexible coordinated beamforming (FlexCoBF) for the downlink of multi-user MIMO systems in single and clustered multiple cells,'' Elsevier Signal Processing, vol. 93, pp. 2462-2473, Sept. 2013. pdf

 

Matlab Codes and Tools:

 

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