Cross-layer optimization is an essential tool for designing wireless network protocols. We present a cross-layer optimization framework for wireless networks where at each node, various smart antenna techniques such as beam-forming, spatial division multiple access and spatial division multiplexing are employed. These techniques provide interference suppression, capability for simultaneous communication with several nodes and transmission with higher data rates, respectively. By
integrating different combinations of these multi-antenna techniques in physical layer with various constraints from MAC and network layers, three Mixed Integer Linear
Programming models are presented to minimize the scheduling period. Since these optimization problems are combinatorially complex, the optimal solution is approached by a Column Generation (CG) decomposition method. Our numerical results show that the resulted directive, multiple access and multiplexing gains combined
with scheduling, effectively increase both the spatial reuse and the capacity of the links and therefore enhance the achievable system throughput.

The introduced cross-layer approach is also extended to consider heterogeneous networks where we present a multi-criteria optimization framework to model the design problem with an objective of jointly minimizing the cost of deployment and the scheduling period. Our results reveal the significant benefits of this joint design method.

We also investigate the achievable performance gain that network coding (with opportunistic listening) when combined with Successive Interference Cancellation (SIC) brings to a multi-hop wireless network. We develop a cross-layer formulation in which SIC enables concurrent receptions from multiple transmitters and network coding reduces the transmission time-slot for minimizing the scheduling time. To solve this combinatorially complex non-linear problem, we decompose it to two linear sub-problems; namely opportunistic network coding aware routing, and scheduling
sub-problems. Our results affirm our expectation for a remarkable performance improvement when both techniques are jointly used.

Further, we develop an optimization model for combining SIC with power control (PC). Our model optimally adjusts the transmission power of nodes to avoid interference on unintended receivers and properly embraces undesired interference through SIC. Therefore, it provides a balance between usage of PC and SIC at the transmitting and receiving sides, respectively. Our results show considerable
throughput improvement in dense and heavily loaded networks.