In this paper, we develop a unifying optimization formulation to describe the Dynamic Channel and Power Assignment (DCPA) problem and an evaluation method for comparing DCPA algorithms. DCPA refers to the allocation of transmit power and frequency channels to links in a cognitive network so as to maximize the total number of feasible links 123 278 J. D. Deaton et al.while minimizing the aggregate transmit power. We apply our evaluation method to five representative DPCA algorithms proposed in the literature. This comparison illustrates the tradeoffs between control modes (centralized versus distributed) and channel/power assignment techniques. We estimate the complexity of each algorithm. Through simulations, we evaluate the effectiveness of the algorithms in achieving feasible link allocations in the network, and their power efficiency. Our results indicate that, when few channels are available, the effectiveness of all algorithms is comparable and thus the one with smallest complexity should be selected. The Least Interfering Channel and Iterative Power Assignment algorithm does not require cross-link gain information, has the overall lowest run time, and achieves the highest feasibility ratio of all the distributed algorithms; however, this comes at a cost of higher average power per link.
In this paper, we develop a unifying optimization formulation to describe the Dynamic Channel and Power Assignment (DCPA) problem and an evaluation method for comparing DCPA algorithms. DCPA refers to the allocation of transmit power and frequency channels to links in a cognitive network so as to maximize the total number of feasible links while minimizing the aggregate transmit power. We apply our evaluation method to five 123 6 J. D. Deaton et al.representative DPCA algorithms proposed in the literature. This comparison illustrates the tradeoffs between control modes (centralized versus distributed) and channel/power assignment techniques. We estimate the complexity of each algorithm. Through simulations, we evaluate the effectiveness of the algorithms in achieving feasible link allocations in the network, and their power efficiency. Our results indicate that, when few channels are available, the effectiveness of all algorithms is comparable and thus the one with smallest complexity should be selected. The Least Interfering Channel and Iterative Power Assignment algorithm does not require cross-link gain information, has the overall lowest run time, and achieves the highest feasibility ratio of all the distributed algorithms; however, this comes at a cost of higher average power per link.
Ultra-wideband (UWB) technology is being proposed for several short range wireless applications. Some of the applications, such as position location devices for rescue personnel, may require the antenna height to be close to the ground. In scenarios where the antenna height is very low (from 0 to 30 cm), propagation characteristics and channel modeling are needed to provide important insights for the application design. This paper presents time-domain measurements and channel characterization of the indoor UWB channel at three different antenna heights (7.5 cm, 26.5 cm, and 108.5 cm). The transmitting and receiving antennas are placed at heights referred to as near ground, middle ground, and above ground. The effects of the antenna height on the channel characteristics are analyzed. Both large and small-scale characteristics are evaluated and the results for different antenna heights are compared. The results show that large scale characteristics exhibit monotonic behavior with respect to antenna height while small scale characteristics do not follow this behavior. The possible explanations for the obtained results are also discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.