Abstract-In this paper, the problem of resource allocation optimization is studied for a single-cell multiuser cognitive radio network in the presence of primary user networks. The spectral access of the cognitive radio network is based on Orthogonal Frequency Division Multiple Access (OFDMA). A joint bandwidth and power allocation is performed so that users' rate requirements are satisfied, and the integrity of primary user communication is preserved. In this work, two unique challenges are addressed. The first is the incorporation of primary user activity in the design of resource allocation technique, and the second is the limited hardware capabilities of cognitive terminals compared to those available at the cognitive base station. To address these problems, a novel resource allocation framework is proposed based on the bandwidth-power product minimization, which is an effective metric in evaluating the spectral resource consumption in a cognitive radio environment. The framework takes into consideration the challenges aforementioned. The results show significant enhancement in spectral efficiency by using our framework compared to classical power adaptive optimization using iterative waterfilling scheme.

This paper presents a conceptual design of a multizone hvac controller based on a wireless sensor network that aims to optimize energy consumption while maintaining the comfort level of users. The proposed system is capable of learning the occupancy pattern of the residents in the building. Moreover, it is transparent (requires no manual configuration). Wireless sensor network technology is used to collect the required measurements for the control system. simulation results are used to demonstrate the system performance in terms of power consumption and comfort level. Additionally, a comparison between the proposed system and other hvac control systems is presented. The results show that the proposed system is capable of providing a major energy savings.I. INTRODUCTION There is an increasing demand for Heat Ventilating and Air Conditioning (HVAC) systems due to the increasing population and global warming and many other serious reasons. Energy conservation becomes a very important problem to be addressed as it affects the local and global quality of life.Researches have made efforts to improve air quality produced by HVAC units [1][2][3]. However, to date there is no cost efficient commercial utilization of this technology. HVAC systems are large consumers of energy, resulting in high electricity bills. HVAC systems consume around 5000 of the total electrical energy generated in the world [4]. Hence, it is very important to optimize the energy consumption of the HVAC system by maximizing energy utilization. Recent studies showed that commercial buildings could reduce energy usage between 15% and 400O by closer monitoring and managing its energy usage [5]. The centralized control of HVAC system has an inherited weakness by allowing the energy to be distributed equally around the serviced zones. This causes a considerable amount of energy to be wasted. Therefore, an intelligent HVAC control is required to minimize the energy consumption and optimize the comfort level.Several studies have been conducted to optimize the energy consumption of HVAC systems [6][7][8][9]. However, these systems are not adaptive to user behaviors [6,7] or they are too complicated to be implemented in a simple embedded system if they are used for multizone buildings [8,9].Although there are some advanced control solutions that provides programmable configuration such as operation time and multiple set points, these systems fail to achieve their main purpose, energy saving, for several reasons. First, these programmable controllers require product education. The limited interface associated with these systems drives the customers to read the product operating manual to figure out how to configure the system to work according to their preferences. Moreover, these controllers are not adaptive. They adhere to the manufacturer's configuration and do not adapt to the customers changing schedule or other new activities that require reconfiguring the system to accommodate these updates. Therefore, many people end up using these programmable system...

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