  In this paper, we study the distributed computational capabilities of
device-to-device (D2D) networks. A key characteristic of D2D networks is that
their topologies are reconfigurable to cope with network demands. For
distributed computing, resource management is challenging due to limited
network and communication resources, leading to inter-channel interference. To
overcome this, recent research has addressed the problems of wireless
scheduling, subchannel allocation, power allocation, and multiple-input
multiple-output (MIMO) signal design, but has not considered them jointly. In
this paper, unlike previous mobile edge computing (MEC) approaches, we propose
a joint optimization of wireless MIMO signal design and network resource
allocation to maximize energy efficiency. Given that the resulting problem is a
non-convex mixed integer program (MIP) which is prohibitive to solve at scale,
we decompose its solution into two parts: (i) a resource allocation subproblem,
which optimizes the link selection and subchannel allocations, and (ii) MIMO
signal design subproblem, which optimizes the transmit beamformer, transmit
power, and receive combiner. Simulation results using wireless edge topologies
show that our method yields substantial improvements in energy efficiency
compared with cases of no offloading and partially optimized methods and that
the efficiency scales well with the size of the network.
