Power allocation for coordinated multi-cell systems with imperfect channel and battery-capacity-limited receivers

This letter studies the transmit power allocation in downlink coordinated multi-cell systems with the batterycapacity-limited receivers, where the battery level of receivers is considered. The power allocation is formulated as an optimization problem to maximize the minimum signal-to-interference noise ratio of users under the per-base station power constraints and the feasible maximum received data rate constraints determined by the receiver battery level. The optimal solutions are derived by the proposed monotonic optimization technique based algorithm. The proposed algorithm can extend the battery lifetime of the receivers with lower battery level. Simulation results illustrate the performance of the proposed algorithm

Power allocation for coordinated multi-cell systems with imperfect channel and battery-capacity-limited receivers

This letter studies the transmit power allocation in downlink coordinated multi-cell systems with the batterycapacity-limited receivers, where the battery level of receivers is considered. The power allocation is formulated as an optimization problem to maximize the minimum signal-to-interference noise ratio of users under the per-base station power constraints and the feasible maximum received data rate constraints determined by the receiver battery level. The optimal solutions are derived by the proposed monotonic optimization technique based algorithm. The proposed algorithm can extend the battery lifetime of the receivers with lower battery level. Simulation results illustrate the performance of the proposed algorithm

Compressive Sensing-Based User Clustering for Downlink NOMA Systems with Decoding Power

This letter investigates joint power control and user clustering for downlink nonorthogonal multiple access systems. Our aim is to minimize the total power consumption by taking into account not only the conventional transmission power but also the decoding power of the users. To solve this optimization problem, it is firstly transformed into an equivalent problem with tractable constraints. Then, an efficient algorithm is proposed to tackle the equivalent problem by using the techniques of reweighted ell -1 -norm minimization and majorization-minimization. Numerical results validate the superiority of the proposed algorithm over the conventional algorithms including the popular matching-based algorithm

Distributed Energy and Resource Management for Full-Duplex Dense Small Cells for 5G

We consider a multi-carrier and densely deployed small cell network, where small cells are powered by renewable energy source and operate in a full-duplex mode. We formulate an energy and traffic aware resource allocation optimization problem, where a joint design of the beamformers, power and sub-carrier allocation, and users scheduling is proposed. The problem minimizes the sum data buffer lengths of each user in the network by using the harvested energy. A practical uplink user rate-dependent decoding energy consumption is included in the total energy consumption at the small cell base stations. Hence, harvested energy is shared with both downlink and uplink users. Owing to the non-convexity of the problem, a faster convergence sub-optimal algorithm based on successive parametric convex approximation framework is proposed. The algorithm is implemented in a distributed fashion, by using the alternating direction method of multipliers, which offers not only the limited information exchange between the base stations, but also fast convergence. Numerical results advocate the redesigning of the resource allocation strategy when the energy at the base station is shared among the downlink and uplink transmissions.Comment: In Proc. of IEEE IWCMC-2017, Valencia, Spain, Jun. 201

Estudi bibliomètric segon trimestre 2014. EETAC

El present document recull les publicacions indexades a la base de dades Scopus durant el període comprès entre el mesos de maig a setembre de l’any 2014, escrits per autors pertanyents a l’EETAC. Es presenten les dades recollides segons la font on s’ha publicat, els autors que han publicat, i el tipus de document publicat. S’hi inclou un annex amb la llista de totes les referències bibliogràfiques publicades.Postprint (published version

Estudi bibliomètric any 2014. Campus del Baix Llobregat: EETAC i ESAB

En el present informe s’analitza la producció científica de les dues escoles del Campus del Baix Llobregat, l’Escola d’Enginyeria de Telecomunicació i Aerospacial de Castelldefels (EETAC) i l’Escola Superior d’Agricultura de Barcelona (ESAB) durant el 2014.Postprint (author’s final draft

User grouping and resource allocation in multiuser MIMO systems under SWIPT

This paper considers a broadcast multiple-input multiple-output (MIMO) network with multiple users and simultaneous wireless information and power transfer (SWIPT). In this scenario, it is assumed that some users are able to harvest power from radio frequency (RF) signals to recharge batteries through wireless power transfer from the transmitter, while others are served simultaneously with data transmission. The criterion driving the optimization and design of the system is based on the weighted sum rate for the users being served with data. At the same time, constraints stating minimum per-user harvested powers are included in the optimization problem. This paper derives the structure of the optimal transmit covariance matrices in the case where both types of users are present simultaneously in the network, particularizing the results to the cases where either only harvesting nodes or only information users are to be served. The trade-off between the achieved weighted sum rate and the powers harvested by the user terminals is analyzed and evaluated using the rate-power (R-P) region. Finally, we propose a two-stage user grouping mechanism that decides which users should be scheduled to receive information and which users should be configured to harvest energy from the RF signals in each particular scheduling period, this being one of the main contributions of this paper.Peer ReviewedPostprint (published version

Energy-aware broadcast multiuser-MIMO precoder design with imperfect channel and battery knowledge

This paper addresses the problem of resource allocation and precoder design in a multiuser MIMO broadcast system where the terminals are battery-powered devices provided with energy harvesting capabilities. Energy harvesting is a promising technology based on which it is possible to recharge the battery of the terminals using energy collected from the environment. Models for the power consumption of the front-end and decoding stages are discussed and included in the design of the proposed scheme. In addition, the information concerning the battery level plays an explicit role and has an impact on the design of our proposed allocation strategy. Sum-rate maximization is considered as optimization policy and energy-related constraints are taken into account explicitly in the resource allocation in order to increase the lifetime of the batteries. In the first part of the paper, we consider the transmitter to have perfect channel state information (CSI) and battery knowledge, assuming an ideal feedback link. Then, a robust design based on imperfect channel information at the transmitter is studied and its effect on the energy consumed by the terminals is analyzed. Finally, an extended robust approach considering also imperfect battery knowledge (quantized battery status) at the transmitter is also addressed. Simulation results show that our proposed technique not only improves the usage of the batteries when compared with other traditional allocation policies, but also enhances the average data ratePeer Reviewe