In this paper, we investigate the problem of spectrum sensing in cognitive radio networks. Compared with related work that aims to propose techniques at different layers of the network protocol stack for detecting primary users, we aim to investigate the capabilities and limitations of different primary user detection techniques from the perspective of network optimization. The goal is to understand the fundamental performance tradeoffs of different primary user detection techniques without being limited by existing cognitive radio software and hardware platforms. To proceed, we first identify several dimensions for designing primary user detection techniques in cognitive radio networks, and then formulate primary user detection techniques using mixed- integer nonlinear programming (MINLP). Evaluation results show the benefits of using the proposed optimization framework for profiling the fundamental characteristics of primary user detection techniques.

In this paper, we investigate the problem of primary user detection in cognitive radio networks. Compared with related work that aims to propose techniques at different layers of the network protocol stack for detecting primary users, we aim to investigate the capabilities and limitations of different primary user detection techniques from the perspective of network optimization. The goal is to understand fundamental performance tradeoffs of these techniques without being limited by existing cognitive radio software and hardware platforms. To proceed, we first identify several dimensions for designing primary transmitter detection techniques in cognitive radio networks, including transmitter side vs. receiver side detection, and collaborative vs. non-collaborative detection. We then formulate primary transmitter detection techniques along these dimensions using mixed-integer nonlinear programming (MINLP). Evaluation results show the benefits of using the proposed optimization framework to profile the fundamental characteristics of primary transmitter detection techniques, thus motivating future research along this direction.

Scaling of the bit size in conventional magnetic recording media is becoming increasingly difficult due to the superparamagnetic limit. Innovations in magnetic recording technology are emerging to enable the continued growth in bit areal density. Thermal stability problems of conventional granular media can be greatly helped by patterning single domain magnetic islands for each magnetic bit. Fabrication of patterned media requires application of nanoimprint lithography for high-volume production of patterned media disks and high-resolution electron beam lithography for fabrication of the nanoimprint masters. We discuss the approaches and the many challenges to the implementation of patterned media disks.

In this paper, we consider multi-mode, multi-radio wireless mesh networks and investigate the impact when multiple wireless mesh networks overlap in service area. We formulate the problem of resource sharing as a network optimization problem, and present a general LP (linear programming) formulation for modeling the problem. We first find that in a system with multiple wireless mesh networks in overlap, individual mesh networks could suffer from capacity degradation if no form of inter-domain coordination is present. Therefore, it is desirable to "interwork" these wireless mesh networks by allowing inter-domain traffic relay through provisioning of "bridge" nodes. If bridge nodes are chosen arbitrarily without any careful planning, however, serious inefficiency and unfairness problem may result. We use the proposed LP formulation to show the impact of bridge node selection and performance tradeoffs between throughput unfairness and network capacity when interworking multiple wireless mesh networks. Based on simulation results, we conclude that if proper interworking is provided, significant performance gain can be obtained for overlapping wireless mesh networks.