Examinando por Autor "Giannakis, Georgios B."

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A Unified Approach to QoS-Guaranteed Scheduling for Channel-Adaptive Wireless Networks
(IEEE, 2007-12-01) Wang, Xin; Giannakis, Georgios B.; Marques, Antonio G.
Scheduling amounts to allocating optimally channel, rate and power resources to multiple connections with diverse quality-of-service (QoS) requirements. It constitutes a throughput-critical task at the medium access control layer of today's wireless networks that has been tackled by seemingly unrelated information-theoretic and protocol design approaches. Capitalizing on convex optimization and stochastic approximation tools, the present paper develops a unified framework for channel-aware QoS-guaranteed scheduling protocols for use in adaptive wireless networks whereby multiple terminals are linked through orthogonal fading channels to an access point, and transmissions are (opportunistically) adjusted to the intended channel. The unification encompasses downlink and uplink with time-division or frequency-division duplex operation; full and quantized channel state information comprising a few bits communicated over a limited-rate feedback channel; different types of traffic (best effort, non-real-time, real-time); uniform and optimal power loading; off-line optimal scheduling schemes benchmarking fundamentally achievable rate limits; as well as on-line scheduling algorithms capable of dynamically learning the intended channel statistics and converging to the optimal benchmarks from any initial value. The take-home message offers an important cross-layer design guideline: judiciously developed, yet surprisingly simple, channel-adaptive, on-line schedulers can approach information-theoretic rate limits with QoS guarantees.
Dynamic Resource Management for Cognitive Radios Using Limited-Rate Feedback
(2009-07-06T13:10:40Z) García Marqués, Antonio; Wang, Xin; Giannakis, Georgios B.
Tailored for the emerging class of cognitive radio networks comprising primary and secondary wireless users, the present paper deals with dynamic allocation of sub-carriers, rate and power resources based on channel state information (CSI) for orthogonal frequency-division multiple access (OFDMA). Users rely on adaptive modulation, coding and power modes that they select in accordance with the limited-rate feedback they receive from the access point. The access point uses CSI to maximize a generic concave utility of the average rates in the network while adhering to rate and power constraints imposed on the primary and secondary users to respect cognitive radio related hierarchies. When the channel distribution is available, optimum dual prices are found to optimally allocate resources across users dynamically per channel realization. In addition, a simple yet optimal on-line algorithm that does not require knowledge of the channel distribution and iteratively computes the dual prices per channel realization is developed using a stochastic dual approach. Analysis of the computational and feedback overhead along with simulations assessing the performance of the novel algorithms are also provided.
Energy Efficient MISO Systems Using Adaptive Modulation and Coding
(2006-11-01T09:13:12Z) Garcia Marques, Antonio; Wang, Xin; Giannakis, Georgios B.
By viewing the coherent wireless sensor network (WSN) setup as a distributed space-time multi-input singleoutput (MISO) system, we minimize average transmit-power when sensors communicate with a fusion center (FC) using adaptive modulation and coding over a wireless fading channel. To this end, we derive optimal distributed beamforming and resource allocation strategies when the full (F-) channel state information at the transmitters (CSIT) is available, or, each sensor has F-CSIT of its own link with the FC but only quantized CSIT of other sensors through finite-rate feedback. Numerical results are presented to evaluate the power savings of the novel strategies.
Energy-Efficient Quantization and Resource Allocation for TDMA with Finite Rate Feedback
(IEEE, 2008-09-01) Wang, Xin; Marques, Antonio G.; Giannakis, Georgios B.
We deal with energy efficient time-division multiple access (TDMA) over fading channels with finite-rate feedback for use in the power-limited regime. Through finite-rate feedback from the access point, users acquire quantized channel state information. The goal is to map channel quantization states to adaptive modulation and coding modes and allocate optimally time slots to users so that the total average transmit-power is minimized. To this end, we develop a joint quantization and resource allocation approach, which decouples the complicated problem at hand into three minimization sub-problems and relies on a coordinate descent approach to iteratively effect energy efficiency. A sub-optimal yet simplified alternative algorithm which decouples the original problem into two sub-problems is also presented. Numerical results are presented to evaluate the energy savings and compare the novel approaches.
Energy-Efficient TDMA with Quantized Channel State Information
(2006-06-01T09:35:20Z) Garcia Marques, Antonio; Wang, Xin; Giannakis, Georgios B.
We deal with energy efficient time-division multiple access (TDMA)over fading channels with finite-rate feedback in the power-limited regime. Through finite-rate feedback from the access point, users acquire quantized channel state information. The goal is to map channel quantization states to adaptive modulation and coding (AMC) modes and allocate optimally time slots to users so that transmitpower is minimized. To this end, we develop two joint quantization and resource allocation approaches. In the first one, we rely on the quantization regions associated to each AMC mode and the time allocation policy inherited from the perfect CSI case to optimize the fixed transmit-power across quantization states. In the second approach,we pursue separable optimization and resort to coordinate descent algorithms to solve the following two sub-problems: (a)given a time allocation, we optimize the quantization regions and transmit-powers; and (b) with improved quantization regions, we optimize the time allocation policy. Numerical results are present to evaluate the energy savings and compare the novel approaches.
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.
Minimizing Transmit-Power for Coherent Communications in Wireless Sensor Networks using Quantized Channel State Information
(2007-04-16T10:00:18Z) Garcia Marques, Antonio; Wang, Xin; Giannakis, Georgios B.
We consider minimizing average transmit-power with finite-rate feedback for coherent communications in a wireless sensor network (WSN), where sensors communicate with a fusion center(FC)using adaptive modulation and coding over a wireless fading channel. By viewing the coherent WSN setup as a distributed space-time multi-input single-output (MISO) system, we develop beamforming and resource allocation strategies and design optimal quantizers when the sensors only have available quantized (Q-) channel state information at the transmitters (CSIT) through a finite-rate feedback channel. Numerical results reveal that our novel design based on Q-CSIT yields significant power savings even for a small number of feedback bits.
Minimizing Transmit-Power for Coherent Communications in Wireless Sensor Networks with Finite-Rate Feedback
(IEEE, 2008-09-01) Marques, Antonio G.; Wang, Xin; Giannakis, Georgios B.
We minimize average transmit power with finite-rate feedback for coherent communications in a wireless sensor network (WSN), where sensors communicate with a fusion center using adaptive modulation and coding over a wireless fading channel. By viewing the coherent WSN setup as a distributed space¿time multiple-input single-output (MISO) system, we present optimal distributed beamforming and resource allocation strategies when the full (F-) channel state information at the transmitters (CSIT) is available through a feedback channel. We also develop optimal adaptive transmission policies and design optimal quantizers for the finite-rate feedback case where the sensors only have quantized (Q-) CSIT, or, each sensor has F-CSIT of its own link with the FC but only Q-CSIT of other sensors. Numerical results confirm that our novel finite-rate feedback-based strategies achieve near-optimal power savings based on even a small number of feedback bits.
Optimal stochastic dual resource allocation for cognitive radios based on quantized CSI
(2008-04-01T10:11:32Z) Garcia Marques, Antonio; Wang, Xin; Giannakis, Georgios B.
The present paper deals with dynamic resource management based on quantized channel state information(CSI)for multicarrier cognitive radio networks comprising primary and secondary wireless users. For each subcarrier, users rely on adaptive modulation, coding and power modes that they select in accordance with the limited-rate feedback they receive from the access point. The access point uses CSI to maximize the sum of generic concave utilities of the individual average rates in the network while respecting rate and power constraints on the primary and secondary users. Using a stochastic dual approach, optimum dual prices are found to optimally allocate resources across users per channel realization without requiring knowledge of the channel distribution.
Optimizing Energy-Efficient of TDMA with Finite Rate Feedback
(2007-04-16) Garcia Marques, Antonio; Wang, Xin; Giannakis, Georgios B.
We deal with energy efficient time-division multiple access (TDMA) over fading channels with finite-rate feedback (FRF) for use in the power-limited regime. Through FRF from the access point, users acquire quantized channel state information. The goal is to map channel quantization states to adaptive modulation and coding modes and allocate optimally time slots to users so that the total average transmit-power is minimized. To this end, we develop a joint quantization and resource allocation approach, which decouples the complicated problem at hand into three minimization sub-problems and relies on a coordinate descent approach to iteratively effect energy efficiency. Numerical results are presented to evaluate the energy savings.
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.
Optimum Scheduling for Orthogonal Multiple Access over Fading Channels using Quantized Channel State Information
(2008-07-01T10:38:31Z) Garcia Marques, Antonio; Giannakis, Georgios B.; Ramos, Javier
The efficiency of multi-access communications over wireless fading links benefits from channel-adaptive allocation of the available bandwidth and power resources. Different from most existing approaches that allocate resources based on perfect channel state information (P-CSI), this work optimizes channel scheduling and resource allocation over orthogonal fading channels when user terminals and the scheduler rely on quantized channel state information (Q-CSI). The novel unifying approach optimizes an average transmit-performance criterion subject to average quality of service requirements. The resultant optimal policy per fading realization either allocates the entire channel to a single (winner) user, or, to a small group of winner users whose percentage of shared resources is found by solving a linear program. Both alternatives become possible by smoothing the allocation scheme. The smooth policy is asymptotically optimal and incurs reduced computational complexity.
Power Control for Cooperative Dynamic Spectrum Access Networks with Diverse QoS Constraints
(2009-07-29T13:11:04Z) Gatsis, Nikolaos; Garcia Marques, Antonio; Giannakis, Georgios B.
Dynamic spectrum access (DSA) is an integral part of cognitive radio technology aiming at efficient management of the available power and bandwidth resources. The present paper deals with cooperative DSA networks, where collaborating terminals adhere to diverse (maximum and minimum) quality-of-service (QoS) constraints in order to not only effect hierarchies between primary and secondary users but also prevent abusive utilization of the available spectrum. Peer-to-peer networks with co-channel interference are considered in both single- and multi-channel settings. Utilities that are functions of the signal-tointerference- plus-noise-ratio (SINR) are employed as QoS metrics. By adjusting their transmit power, users can mitigate the generated interference and also meet the QoS requirements. A novel formulation accounting for heterogeneous QoS requirements is obtained after introducing a suitable relaxation and recasting a constrained sum-utility maximization as a convex optimization problem. The optimality of the relaxation is established under general conditions. Based on this relaxation, an algorithm for optimal power control that is amenable to distributed implementation is developed, and its convergence is established. Numerical tests verify the analytical claims and demonstrate performance gains relative to existing schemes.
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 Resource Allocation and Quantization for TDMA Using Adaptive Transmission and Limited-Rate Feedback
(2008-09-01T08:59:09Z) Wang, Xin; Garcia Marques, Antonio; Giannakis, Georgios B.
Power-efficient scheduling and resource allocation are critical tasks for wireless sensor networks as well as commercial and tactical radios relying on IEEE access standards for power-limited communications. Tailored for such applications, this paper formulates and solves analytically novel convex optimization problems offering globally optimal user scheduling, as well as rate and power allocation for time-division multiple access (TDMA)in time-division-duplex or frequency-division-duplex operation. Through a limited-rate feedback link the access point provides quantized channel state information to the transmitters (Q-CSIT)based on which users adapt their modulation and code choices to the intended fading channel. When the quantizer needed to form the Q-CSIT is not prescribed, a joint allocation-quantization scheme is devised to minimize average transmit power subject to average rate and bit error rate constraints. The novel design couples adaptive transmission modes with quantization regions which are constructed to attain at least a local minimum of the average transmit power. Fairness in resource allocation is guaranteed by design. Transmit power and quantization region books are efficiently obtained offline while the online Q-CSIT based operation turns out to entail only a few feedback bits. Analysis and simulations include a perfect CSIT benchmark and reveal substantial power savings (as high as 15 dB) with low-overhead feedback.
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.
Stochastic resource allocation for orthogonal access based on quantized CSI: optimality, convergence and delay analysis
(2009-04-01T11:29:29Z) Garcia Marques, Antonio; Giannakis, Georgios B.; Ramos, Javier
Dynamic allocation of power, rate and channel access is a critical task in wireless networks. Capitalizing on convex optimization and stochastic approximation tools, this paper develops a stochastic resource allocation algorithm that minimizes average transmit power under individual average rate constraints. Focus is placed on networks where users transmit orthogonally over a set of parallel channels and transmissions are adapted based on quantized channel state information (CSI) allowing even channel statistics to be unknown. Convergence of the developed stochastic scheme is characterized and the average queue delays are obtained in closed form.
Utility-Based Power Control for Peer-to-Peer Cognitive Radio Networks with Heterogeneous QoS Constraints
(2008-04-01T11:42:41Z) Gatsis, Nikolaos; Garcia Marques, Antonio; Giannakis, Georgios B.
Transmit-power control is a critical task in cognitive radio (CR)networks. In the present contribution, adherence to hierarchies between primary and secondary users in a peer-to-peer CR network is enabled through distributed power control. Hierarchies are effected by imposing minimum and maximum bounds on a quality-of-service(QoS) metric, such as communication rate.These bounds translate to signal-to-interference-plus-noise ratio (SINR) constraints. Furthermore, a utility function captures each user's satisfaction with the received SINR. The novel power control strategy maximizes the total utility while respecting individual SINR constraints - a task recast as a convex optimization problem under a suitable relaxation. Sufficient conditions, realistic for practical CR networks, are provided to obtain the optimal power allocation from the solution of the relaxed problem. Finally, a low-overhead distributed algorithm for optimal power control is developed, and tested against competing alternatives via simulations.