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. ; Work in this paper was supported by the ARO Grant W911NF-05-1-0283 and was prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The work of A. G. Marques in this paper was partially supported by the C.A. Madrid Government Grant P-TIC-000223-0505. ; Teor?a de la Se?al y Comunicaciones
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. ; Work in this paper was supported by the ARO Grant W911NF-05-1-0283 and was prepared through collaborative participation in the Communications and Networks Consortium sponsored by the U.S. Army Research Laboratory under the Collaborative Technology Alliance Program, Cooperative Agreement DAAD19-01-2-0011. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon. The work of A. G. Marques in this paper was partially supported by the C.A. Madrid Government Grant P-TIC-000223-0505. ; Teor?a de la Se?al y Comunicaciones
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. ; The work of A. G. Marques was supported in part by the Spanish Government under Grant TEC2005-06766-C03-01/TCM. This work was supported in part by the USDoD ARO under Grant W911NF-05-1-0283. ; Teor?a de la Se?al y Comunicaciones
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. ; The work in this paper was supported by the US ARL under the CTA Program, Cooperative Agreement No. DAAD19-01-2-0011; by USDoD ARO grant No. W911NF-05-1-0283; by Spanish Government grant No. TEC2005-06766-C03-01/TCM, and by the Government of C.A. Madrid grant No. P-TIC-000223-0505. ; Teor?a de la Se?al y Comunicaciones
Over the last several years, a great amount of research work has been focused on the development of model predictive control techniques for the indoor climate control of buildings, but, despite the promising results, this technology is still not adopted by the industry. One of the main reasons for this is the increased cost associated with the development and calibration (or identification) of mathematical models of special structure used for predicting future states of the building. We propose a methodology to overcome this obstacle by replacing these hand-engineered mathematical models with a thermal simulation model of the building developed using detailed thermal simulation engines such as EnergyPlus. As designing better controllers requires interacting with the simulation model, a central part of our methodology is the control improvement (or optimisation) module, facilitating two simulation-based control improvement methodologies: one based in multi-criteria decision analysis methods and the other based on state-space identification of dynamical systems using Gaussian process models and reinforcement learning. We evaluate the proposed methodology in a set of simulation-based experiments using the thermal simulation model of a real building located in Portugal. Our results indicate that the proposed methodology could be a viable alternative to model predictive control-based supervisory control in buildings. ; Research leading to these results has been partially supported by the Modelling Optimization of Energy Efficiency in Buildings for Urban Sustainability (MOEEBIUS) project. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 680517. Georgios Giannakis and Dimitrios Rovas gratefully acknowledge financial support from the European Commission H2020-EeB5-2015 project "Optimised Energy Efficient Design Platform for Refurbishment at District Level" under Contract #680676 (OptEEmAL). Georgios Kontes and Christopher Mutschler gratefully acknowledge financial support from the Federal Ministry of Education and Research of Germany in the framework of Machine Learning Forum (grant number 01IS17071). Georgios Kontes, Natalia Panagiotidou, Simone Steiger and Gunnar Gruen gratefully acknowledge use of the services and facilities of the Energie Campus Nürnberg. The APC was funded by MOEEBIUS project. This paper reflects only the authors' views and the Commission is not responsible for any use that may be made of the information contained therein.
Summarization: An innovative multi-criteria methodology was proposed for the prioritization of the Program of Measures (PoM) in the Water Region of Crete, and applied specifically to the basin of Geropotamos river according to the requirements of the Water Framework Directive. This study relied on the four pillars of sustainability and the EU cross-compliance legislative objective for the minimization of the climate change impact. The multi-criteria evaluation methodology was based on the results of four different types of analyses: a DPSIR analysis, a SWOT analysis, a Cost-Benefit Analysis and a climate change impacts analysis. Public participation on the results of the study with local stakeholders was used at every stage of the multi-criteria evaluation process, from the selection and weighing of the criteria to the final ranking and measures' prioritization. The PoM contains two types of measures: basic measures which deal with the implementation of existing legislation and are the same for all regions of Greece and additional measures which are specified for the Region of Crete. The results of the prioritization process in Geropotamos Basin suggests that improving the water quality and ecological status of available water resources do not always require significant financial resources and can have a high impact in terms of achieving "good" quality status. ; Παρουσιάστηκε στο: Science of the Total Environment