John Paul Torregoza

Joint power control, base station assignment, and channel assignment in cognitive femtocell networks

Cognitive radio and femtocells are recent technology breakthroughs that aim to achieve throughput improvement by means of spectrum management and interference mitigation, respectively. However, these technologies are limited by the formers susceptibility to interference and the latters dependence on bandwidth availability. In this paper, we overcome these limitations by integrating cognitive radio and femtocell technology and exploring its feasibility and throughput improvement. To realize this, we propose an integrated architecture and formulate a multiobjective optimization problem with mixed integer variables for the joint power control, base station assignment, and channel assignment scheme. In order to find a pareto optimal solution, a weighted sum approach was used. Based on numerical results, the optimization framework is found to be both stable and converging. Simulation studies further show that the proposed architecture and optimization framework improve the aggregate throughput as the client population rises, hence confirming the successful and beneficial integration of these technologies.

A joint power control and converge scheme in a cognitive-femtocell architecture for wireless networks for throughput maximization

Cognitive radio and femtocells are recent technology breakthroughs that aim at achieving throughput improvement by means of spectrum management and interference mitigation, respectively. However, these technologies are limited by the formers susceptibility to interference and the latters dependence on bandwidth availability. In this paper, we overcome these limitations by integrating cognitive radio and femtocell technology and explore the byproducts feasibility and throughput improvement. To realize this, we propose an integrated architecture and optimization framework based on power control, coverage assignment, and compensation schemes. Based on numerical results, the optimization framework is found to be both stable and converging. Simulation studies further show that the proposed architecture and optimization framework improves the aggregate throughput as the client population rises, hence confirming the successful and beneficial integration of these technologies.

An Opportunistic Cross-Layer Architecture for New Generation Networks

Cognitive radio in network core devices such as basestations is being considered as a spectrum management solution for future societys communication demands. Aside from new resource allocation algorithms, efficient inter- and intra-protocol processing should be considered. We propose an opportunistic cross layer architecture called COmmon Layer Architecture (COLA) for information exchange between arbitrary layers for New Generation Networks (NWGN) with network-oriented cognitive radio. Through COLA, information from different protocols, as well as different layers, can be efficiently processed with minimized performance degradation. Emulation and simulation results showed improved aggregate throughput, handoff delay, connectivity and packet drop ratio.

Multi-channel Multi-Transceiver Routing Protocol for Wireless Mesh Network

Wireless mesh networks is a decentralized networking technology that is currently being adapted to connect peer-to-peer clients and large-scale backbone networks. Nodes are designed to act as repeaters allowing communication or very large distances. Robustness is another characteristic of wireless mesh networks, partly due to its decentralized nature which removes a central point of failure. Due to its complex nature, a number of issues are still under research. Broadband communication such as WLAN and UWB are ideal for transmission of mesh data due to their high speed. Researches in the PHY layer have come up with using multi-channel and multi-transceiver technology is being studied to improve the capacity of mesh networks. Routing protocols are also a vital research in mesh networks. Distributed routing is needed which can find the optimized path in a widely decentralized mesh network. Also, with the implementation of new PHY technology, existing routing protocols need to be revised to exploit the advantages of new the new PHY. This paper aims to improve existing protocols for wireless mesh networks and wireless adhoc networks in order to take advantage of the properties of multi-channel technology.

Quality of Service Aware Route Discovery for Wireless Sensor Networks

Traditional wireless sensor networks operate using best-effort regardless of what type of traffic is being transmitted between source and destination. Due to assumed redundancy of sensor data, this method of transmission is considered to be sufficient for transmission of data used in environment monitoring, surveillance, or location- aware applications. Reliability or delay concerns were considered to be general properties of the network and solved regardless of what traffic is being transmitted. Current developments creates the possibly of heterogeneous traffic, that is data which has different priorities of transmission. This introduces the possibility of including quality of service (QoS) parameters in decision making and transmission of data from sensor. This paper explores the idea of incorporating QoS parameters in making routing decisions with concerns on power, reliability and delay. An optimization problem is formulated to determine the optimum data transmission rate with constraints on power, reliability and delay

An opportunistic power and modulation control algorithm for new generation networks

Since the numbers of wireless communication devices will increase significantly in the future, effective frequency utilization technologies are required for efficient and scalable communication while preventing interference. Cognitive radio is expected to be one of such technologies. In particular, network-oriented cognitive radio architecture is key to the adaptability of the network core. In this paper, we propose an opportunistic power and modulation control algorithm for the new generation network in a network-oriented cognitive radio architecture. We formulate a multi-objective mixed integer optimization problem which maximize aggregate throughput and connectivity while minimizing power consumption. Based on the simulation results, the proposed algorithm achieves better performance in terms of aggregate throughput, connectivity and reduced power consumption.

Wireless sensor network renewable energy source life estimation

Sensor applications are gaining popularity in health applications particularly in environmental monitoring and patient monitoring. Some applications include monitoring of C02 concentration in home environment, pulse monitoring for in-house patients, and monitoring of medicine distribution in hospitals. Sensors can be deployed in the target environment or in some cases, worn by the monitored patient. Data from these deployed sensor are then stored in a database for future analysis by medical professionals. Reliability and accuracy of data is considered for medical application. This paper presents a simple model for renewable energy source in the deployed sensors. Using solar energy model concepts and battery mechanism, we stochastically tried to model the behavior of rechargeable energy sources used for wireless sensor networks. This model can then be used as cost function for providing efficient routing and good quality of service.

Wireless Sensor Network Renewable Energy Source Life Estimation

Sensor applications are gaining popularity in health applications particularly in environmental monitoring and patient monitoring. Some applications include monitoring of C02 concentration in home environment, pulse monitoring for in-house patients, and monitoring of medicine distribution in hospitals. Sensors can be deployed in the target environment or in some cases, worn by the monitored patient. Data from these deployed sensor are then stored in a database for future analysis by medical professionals. Reliability and accuracy of data is considered for medical application. This paper presents a simple model for renewable energy source in the deployed sensors. Using solar energy model concepts and battery mechanism, we stochastically tried to model the behavior of rechargeable energy sources used for wireless sensor networks. This model can then be used as cost function for providing efficient routing and good quality of service.