In this paper, we investigate into optimal admission control policies for Heterogeneous Wireless Networks (HWN), considering an integration of wireless mesh networks with an overlaying cellular infrastructure. In order to characterize the overflow traffic from the underlaying mesh to the overlay, a Partially-Observable Markov-Modulated Poisson Process (PO-MMPP) traffic model is developed. This model captures the burstiness of the overflow traffic under the imperfect observability of the mesh network states. Then, by modeling the overlay network as a controlled PO-MMPP/M/C/C queueing system and obtaining structured decision theoretic results, it is shown that the optimal control policies for this class of HWNs can be characterized as monotonic threshold curves. Further, these results are used to design a computationally efficient algorithm to determine the optimal policy in terms of thresholds. Numerical observations suggest that the proposed algorithm is efficient in terms of time-complexity and can drastically reduce the cost of dropped and blocked calls.

In the near future, demand for Heterogeneous Wireless Networking (HWN) is expected to to increase. QoS provisioning in these networks is a challenging issue considering the diversity in wireless networking technologies and the existence of mobile users with different communication requirements. In HWNs with their increased complexity, "the curse of dimensionality" problem makes it impractical to directly apply the decision theoretic optimal control methods that are previously used in homogeneous wireless networks to achieve desired QoS levels. In this paper, optimal call admission control policies for HWNs are considered. A decision theoretic framework for the problem is derived by a dynamic programming formulation. We prove that for a two-tier wireless network architecture, the optimal policy has a two-dimensional threshold-based structure. Further, a novel algorithm called Structured Value Iteration is proposed as a numerically efficient method to determine the optimal policy in terms of its thresholds. Extensive simulation experiments are conducted. The numerical results show that the proposed algorithm is efficient in terms of its time-complexity and in achieving the optimal performance.

In this paper, resource allocation and outage control are considered for solar-powered WLAN mesh networks. Solar-powered nodes are a very cost effective option in WLAN mesh deployments where continuous power sources are not practical. In such nodes, the cost of the solar panel and battery can be a significant fraction of the total and, therefore, reducing AP power consumption is very important. A solar panel/battery configuration methodology is introduced based on a proposed AP power-aware version of IEEE 802.11. Public meteorological data is used to provision each node based on an averaged offered capacity profile. Since a node is configured statistically, it is possible that future loading may result in nonzero outage even when negligible outage is the design target. Control algorithms are introduced which can improve node outage performance by sometimes introducing an access point capacity deficit. Results are presented which show the value of the proposed configuration methodology and show that the control algorithms can prevent outage even at high levels of excess loading.