The LEGO approach for achieving max-min capacity in reciprocal multipoint networks

Locally enabled, globally optimized (LEGO) wireless networks offer paradigm shifting performance enhancements for wireless networks equipped with multiple antennas. In this paper attention is focused on some convergence aspects of an improved version of the LEGO algorithm. A technique is presented which is guaranteed to converge to a local optimum of a newly formulated network objective function, that minimizes the total network transmit power subject to arbitrary channel capacity constraints. Networks that possess channel reciprocity can efficiently implement the LEGO algorithm using highly localized information, obviating the need for complex network controllers. Moreover the LEGO algorithm can efficiently exploit MIMO channel and network topology diversity to multiply the capacity of the network. A numerical experiment is presented which suggests several orders of magnitude performance improvement over more conventional networks.