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Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search., QC 20120312

Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search., QC 20120312

Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search., QC 20120312

Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search., QC 20220209

Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using time-averaged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search., QC 20220209