Cross-Layer Optimization Using Advanced Physical Layer Techniques in Wireless Mesh Networks

Abstract

Abstract-The objective of this paper is to study the impact of advanced physical layer techniques on the maximum achievable throughput of wireless multihop mesh networks. We formulate a cross-layer optimization framework for the routing and scheduling problem jointly with the following physical layer techniques: successive interference cancellation, superposition coding, dirtypaper coding and their combinations. In the case when each node is enabled with superposition coding, we need to formulate a power allocation subproblem for the optimal power partition of the superimposed signals. We solve these joint problems exactly to compute the maximum achievable throughput in realistic size networks. This allows us to quantify the performance gains obtained by using these techniques (and their combinations). Specifically, we find that the use of dirty-paper coding (only at the gateway) is not justified in networks with mixed uplink and downlink flows. On the other hand, the combination of superposition coding with successive interference outperforms significantly other techniques across all transmission power range for both uplink and downlink flows. We also provide a number of interesting practical insights on throughput improvement by comparing different combinations of these techniques.

Routing, Scheduling and Power Allocation in Generic OFDMA Wireless Networks: Optimal Design and Efficiently Computable Bounds

“…However, this replacement affects the capacity constraints in (10e) and the power budget constraints in (10i). Since, from (16), only one element in {p k } L =1 is strictly positive for any subchannel k ∈ K, the constraints in (10e) can be expressed as…”

“…For the constraints in (19f), although the LHSs are in the form of monomials, they are not compatible with the GP framework because their RHSs are not equal to 1. This difficulty can be readily alleviated by replacing (16) with constraints of the form p k p k ≤ , where is a small positive number. This replacement will expand the feasible region of the considered optimization problem in (19).…”

“…Therein, the nodes use superposition coding for transmission and the design is performed using the GP framework. An improvement on the design in [15] is proposed in [16] by allowing the nodes to reduce interference using a successive cancellation technique. Additional performance gains in OFDMA networks have been sought by incorporating more functionalities in the joint design of the network, e.g., [17], [18].…”

An efficient cross layer design for OFDMA-based wireless networks with channel reuse

“…The relaxations in (18g) and (18h) may result in infeasible power allocations that do not satisfy the constraints in (9b) and (10). To construct a feasible, but potentially suboptimal, power allocations, the elements of {q ℓk } that are less than or equal to √ ǫ are set to zero.…”

“…In that case, the optimal routes and power allocations are obtained, provided that the rates are chosen from a discrete set. Cross layer designs that exploit the broadcast feature of the wireless medium were developed in [9] and [10] using superposition coding and optimization techniques, including geometric programming (GP). Techniques for jointly optimizing the power allocations, the subchannel schedules and the data routes were developed in [11], [12] for networks in which subchannel reuse among multiple nodes is not permitted.…”