  Due to the unique physical-layer characteristics associated with MIMO and
cognitive radio (CR), the network performance is tightly coupled with
mechanisms at the physical, link, network, and transport layers. In this paper,
we consider an energy-efficient cross-layer optimization problem in multihop
MIMO CR networks. The objective is to balance the weighted network utility and
weighted power consumption of SU sessions, with a minimum PU transmission rate
constraint and SU power consumption constraints. However, this problem is
highly challenging due to the nonconvex PU rate constraint. We propose a
solution that features linearization-based alternative optimization method and
a heuristic primal recovery method. We further develop a distributed algorithm
to jointly optimize covariance matrix at each transmitting SU node, bandwidth
allocation at each SU link, rate control at each session source and
multihop/multi-path routing. Extensive simulation results demonstrate that the
performance of the proposed distributed algorithm is close to that of the
centralized algorithm, and the proposed framework provides an efficient way to
significantly save power consumption, while achieving the network utility very
close to that achieved with full power consumption.
