
CB‐REFIM: a practical coordinated beamforming in multicell networks
Author(s) -
Akbari Mohammad Hossein,
Vakili Vahid Tabataba
Publication year - 2014
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2013.0907
Subject(s) - beamforming , backhaul (telecommunications) , computer science , mathematical optimization , precoding , computational complexity theory , base station , optimization problem , transmitter power output , overhead (engineering) , mimo , algorithm , mathematics , telecommunications , transmitter , channel (broadcasting) , operating system
Performance of multicell systems is inevitably limited by interference and available resources. Although intercell interference can be mitigated by base station (BS) coordination, the demand on inter‐BS information exchange and computational complexity grows rapidly with the number of cells, subcarriers and users. On the other hand, some of the existing coordination beamforming methods need computation of pseudo‐inverse or generalised eigenvector of a matrix, which are practically difficult to implement in a real system. To handle these issues, the authors propose a novel linear beamforming across a set of coordinated cells only with limiting backhaul signalling. Resource allocation (i.e. precoding and power control) is formulated as an optimisation problem with objective function of signal‐to‐interference‐plus‐noise ratios in order to maximise the instantaneous weighted sum‐rate subject to power constraints. Although the primal problem is non‐convex and difficult to be optimally solved, an iterative algorithm is presented based on the Karush–Kuhn–Tucker condition. To have a practical solution with low computational complexity and signalling overhead, they present CB‐REFIM (coordination beamforming‐reference based interference management) and show the recently proposed reference based interference management algorithm (REFIM) can be interpreted as a special case of CB‐REFIM. They evaluate CB‐REFIM through extensive simulation and observe that the proposed strategies achieve close‐to‐optimal performance.