Examinando por Autor "Digham, Fadel F."

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Minimizing Power in Wireless OFDMA with Limited Rate Feedback
(2007-03-11T09:52:37Z) Garcia Marques, Antonio; Giannakis, Georgios B.; Digham, Fadel F.; Ramos, Javier
Emerging applications involving low-cost wireless sensor networks motivate well optimization of multi-user orthogonal frequency-division multiple access (OFDMA) in the power-limited regime. In this context, the present paper relies on limited-rate feedback (LRF) sent from the access point to terminals to minimize the total average transmit-power under individual average rate and error probability constraints. The characterization of optimal bit, power and subcarrier allocation policies based on LRF, as well as optimal channel quantization are provided. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with few fed back bits.
Optimizing Power Efficiency of OFDM Using Quantized Channel State Information
(IEEE, 2006-08-01) Marques, Antonio G.; Digham, Fadel F.; Giannakis, Georgios B.
Emerging applications involving low-cost wireless sensor networks motivate well optimization of orthogonal frequency-division multiplexing (OFDM) in the power-limited regime. To this end, the present paper develops loading algorithms to minimize transmit-power under rate and error probability constraints, using three types of channel state information at the transmitter (CSIT): deterministic (per channel realization) for slow fading links, statistical (channel mean) for fast fading links, and quantized (Q), whereby a limited number of bits are fed back from the transmitter to the receiver. Along with optimal bit and power loading schemes, quantizer designs and reduced complexity alternatives with low feedback overhead are developed to obtain a suite of Q-CSIT-based OFDM transceivers with desirable complexity versus power-consumption tradeoffs. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with a few bits of Q-CSIT.
Power-Efficient OFDM via Quantized Channel State Information
(2006-06-01T10:47:55Z) Garcia Marques, Antonio; Digham, Fadel F.; Giannakis, Georgios B.
In response to the growing demand for low-cost low-power wireless sensor networks and related applications,we develop bit and power loading algorithms that minimize transmit-power for orthogonal frequency division multiplexing (OFDM) under rate and error probability constraints.Our novel algorithms exploit one of three types of channel state information at the transmitter (CSIT): deterministic (per channel realization)for slow fading links, statistical (channel mean) for fast fading links, and quantized (Q-) CSIT whereby a limited number of bits are fed back from the transmitter to the receiver. By adopting average transmit-power as a distortion metric, a channel quantizer is also designed to obtain a suitable form of Q-CSI. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with a few bits of QCSIT.
Power-Efficient OFDM with Reduced Complexity and Feedback Overhead
(2006-05-01T11:04:53Z) Garcia Marques, Antonio; Digham, Fadel F.; Giannakis, Georgios B.
Motivated by the increasing demand for low-cost low-power wireless sensor networks and related applications, we develop suboptimal but simple bit and power loading algorithms that minimize transmit-power for orthogonal frequency division multiplexing (OFDM) under rate and error probability constraints. Bit and power loading adaptation are based on a quantized version of channel state information (D-CSI) conveyed from the receiver to the transmitter. Our design exploits the correlation among sub-carriers in order to reduce feedback overhead. Numerical examples support our claim that simple suboptimal schemes with a reduced number of feedback bits achieve near-optimal performance while providing significant power savings.
Power-Efficient Wireless OFDMA Using Limited-Rate Feedback
(IEEE, 2008-02-01) Marques, Antonio G.; Giannakis, Georgios B.; Digham, Fadel F.; Ramos, Javier
Emerging applications involving low-cost wireless sensor networks motivate well optimization of multi-user orthogonal frequency-division multiple access (OFDMA) in the power-limited regime. In this context, the present paper relies on limited-rate feedback (LRF) sent from the access point to terminals to minimize the total average transmit-power under individual average rate and error probability constraints. Along with the characterization of optimal bit, power and subcarrier allocation policies based on LRF, suboptimal yet simple schemes are developed for channel quantization. The novel algorithms proceed in two phases: (i) an off-line phase to construct the channel quantizer as well as the rate and power codebooks with moderate complexity; and (ii) an on-line phase to obtain, based on quantized channel state information, the optimum, rate, power and user-subcarrier allocation with linear complexity. Numerical examples corroborate the analytical claims and reveal that significant power savings result even with suboptimal schemes based on practically affordable LRF.
Reduced-Complexity Power-Efficient Wireless OFDMA using an Equally Probable CSI Quantizer
(2007-06-24T11:18:13Z) Garcia Marques, Antonio; Digham, Fadel F.; Giannakis, Georgios B.; Ramos, Javier
Emerging applications involving low-cost wireless sensor networks motivate well optimization of multi-user orthogonal frequency-division multiple access (OFDMA) in the powerlimited regime. In this context, the present paper relies on limitedrate feedback (LRF) sent from the access point to terminals to acquire quantized channel state information (CSI) in order to minimize the total average transmit-power under individual average rate and error probability constraints. Specifically, we introduce two suboptimal reduced-complexity schemes to: (i) allocate power, rate and subcarriers across users; and (ii) design accordingly the channel quantizer. The latter relies on the solution of (i) to design equally probable quantization regions per subcarrier and user. Numerical examples corroborate the analytical claims and reveal that the power savings achieved by our reduced-complexity LRF designs are close to those achieved by the optimal solution.