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Perruisseau-Carrier J.,Catalonia Technology Center of Telecomunications
IEEE Transactions on Antennas and Propagation | Year: 2010

A reflecting cell allowing the dynamic and independent control of the reflection phase of two perpendicular linearly-polarized waves is presented. This capability is useful for the implementation of dual-polarized beam-reconfigurable reflectarrays, as well as for new reflector functionalities such as linear/circular polarization-flexibility and polarization-twisting with simultaneous phase control. The concept is demonstrated on a unit cell operating at 8 GHz, using surface-mounted diodes. In addition to its polarization capability, the cell implements a new concept to overcome the usual tradeoff between phase range and loss in monolayer reflective cells, using a combination of PIN and varactor diodes. For each linearly-polarized component, a dynamic phase range over 360° is achieved at 8 GHz under normal incidence, with 4 dB and 2 dB of maximum and average loss, respectively. The modeling of the cell in a general periodic environment, along with measurements in a waveguide simulator, show that similar performance is preserved within a 5% bandwidth and under TE and TM oblique incidences up to 45°. The cell size is only 0.42λat 8 GHz. © 2006 IEEE. Source


Ng D.W.K.,Friedrich - Alexander - University, Erlangen - Nuremberg | Lo E.S.,Catalonia Technology Center of Telecomunications | Schober R.,Friedrich - Alexander - University, Erlangen - Nuremberg
IEEE Transactions on Wireless Communications | Year: 2013

This paper considers orthogonal frequency division multiple access (OFDMA) systems with simultaneous wireless information and power transfer. We study the resource allocation algorithm design for maximization of the energy efficiency of data transmission (bits/Joule delivered to the receivers). In particular, we focus on power splitting hybrid receivers which are able to split the received signals into two power streams for concurrent information decoding and energy harvesting. Two scenarios are investigated considering different power splitting abilities of the receivers. In the first scenario, we assume receivers which can split the received power into a continuous set of power streams with arbitrary power splitting ratios. In the second scenario, we examine receivers which can split the received power only into a discrete set of power streams with fixed power splitting ratios. For both scenarios, we formulate the corresponding algorithm design as a non-convex optimization problem which takes into account the circuit power consumption, the minimum data rate requirements of delay constrained services, the minimum required system data rate, and the minimum amount of power that has to be delivered to the receivers. By exploiting fractional programming and dual decomposition, suboptimal iterative resource allocation algorithms are developed to solve the non-convex problems. Simulation results illustrate that the proposed iterative resource allocation algorithms approach the optimal solution within a small number of iterations and unveil the trade-off between energy efficiency, system capacity, and wireless power transfer: (1) wireless power transfer enhances the system energy efficiency by harvesting energy in the radio frequency, especially in the interference limited regime; (2) the presence of multiple receivers is beneficial for the system capacity, but not necessarily for the system energy efficiency. © 2002-2012 IEEE. Source


Ng D.W.K.,Friedrich - Alexander - University, Erlangen - Nuremberg | Lo E.S.,Catalonia Technology Center of Telecomunications | Schober R.,Friedrich - Alexander - University, Erlangen - Nuremberg
IEEE Transactions on Wireless Communications | Year: 2014

This paper considers a multiuser multiple-input single-output (MISO) downlink system with simultaneous wireless information and power transfer. In particular, we focus on secure communication in the presence of passive eavesdroppers and potential eavesdroppers (idle legitimate receivers). We study the design of a resource allocation algorithm minimizing the total transmit power for the case when the legitimate receivers are able to harvest energy from radio frequency signals. Our design advocates the dual use of both artificial noise and energy signals in providing secure communication and facilitating efficient wireless energy transfer. The algorithm design is formulated as a non-convex optimization problem. The problem formulation takes into account artificial noise and energy signal generation for protecting the transmitted information against both considered types of eavesdroppers when imperfect channel state information (CSI) of the potential eavesdroppers and no CSI of the passive eavesdroppers are available at the transmitter. Besides, the problem formulation also takes into account different quality of service (QoS) requirements: a minimum required signal-to-interference-plus-noise ratio (SINR) at the desired receiver; maximum tolerable SINRs at the potential eavesdroppers; a minimum required outage probability at the passive eavesdroppers; and minimum required heterogeneous amounts of power transferred to the idle legitimate receivers. In light of the intractability of the problem, we reformulate the considered problem by replacing a non-convex probabilistic constraint with a convex deterministic constraint. Then, a semi-definite programming (SDP) relaxation approach is adopted to obtain the optimal solution for the reformulated problem. Furthermore, we propose a suboptimal resource allocation scheme with low computational complexity for providing communication secrecy and facilitating efficient energy transfer. Simulation results demonstrate the close-to-optimal performance of the proposed schemes and significant transmit power savings by optimization of the artificial noise and energy signal generation. © 2002-2012 IEEE. Source


Ng D.W.K.,Friedrich - Alexander - University, Erlangen - Nuremberg | Lo E.S.,Catalonia Technology Center of Telecomunications | Schober R.,Friedrich - Alexander - University, Erlangen - Nuremberg
IEEE Transactions on Wireless Communications | Year: 2013

We study resource allocation algorithm design for energy-efficient communication in an orthogonal frequency division multiple access (OFDMA) downlink network with hybrid energy harvesting base station (BS). Specifically, an energy harvester and a constant energy source driven by a non-renewable resource are used for supplying the energy required for system operation. We first consider a deterministic offline system setting. In particular, assuming availability of non-causal knowledge about energy arrivals and channel gains, an offline resource allocation problem is formulated as a non-convex optimization problem over a finite horizon taking into account the circuit energy consumption, a finite energy storage capacity, and a minimum required data rate. We transform this non-convex optimization problem into a convex optimization problem by applying time-sharing and exploiting the properties of non-linear fractional programming which results in an efficient asymptotically optimal offline iterative resource allocation algorithm for a sufficiently large number of subcarriers. In each iteration, the transformed problem is solved by using Lagrange dual decomposition. The obtained resource allocation policy maximizes the weighted energy efficiency of data transmission (weighted bit/Joule delivered to the receiver). Subsequently, we focus on online algorithm design. A conventional stochastic dynamic programming approach is employed to obtain the optimal online resource allocation algorithm which entails a prohibitively high complexity. To strike a balance between system performance and computational complexity, we propose a low complexity suboptimal online iterative algorithm which is motivated by the offline algorithm. Simulation results illustrate that the proposed suboptimal online iterative resource allocation algorithm does not only converge in a small number of iterations, but also achieves a close-to-optimal system energy efficiency by utilizing only causal channel state and energy arrival information. © 2002-2012 IEEE. Source


Ng D.W.K.,Friedrich - Alexander - University, Erlangen - Nuremberg | Lo E.S.,Catalonia Technology Center of Telecomunications | Schober R.,Friedrich - Alexander - University, Erlangen - Nuremberg
IEEE Transactions on Wireless Communications | Year: 2012

We study resource allocation for energy-efficient communication in multi-cell orthogonal frequency division multiple access (OFDMA) downlink networks with cooperative base stations (BSs). We formulate the resource allocation problem for joint BS zero-forcing beamforming (ZFBF) transmission as a non-convex optimization problem which takes into account the circuit power consumption, the limited backhaul capacity, and the minimum required data rate. We transform the considered problem in fractional form into an equivalent optimization problem in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. In each iteration, a low-complexity suboptimal semi-orthogonal user selection policy is computed. Besides, by using the concept of perturbation function, we show that in the considered systems under some general conditions, the duality gap with respect to the power optimization variables is zero despite the non-convexity of the primal problem. Thus, dual decomposition can be used in each iteration to derive an efficient closed-form power allocation solution for maximization of the energy efficiency of data transmission (bit/Joule delivered to the users). Simulation results illustrate that the proposed iterative resource allocation algorithm converges in a small number of iterations, and unveil the trade-off between energy efficiency, network capacity, and backhaul capacity: (1) In the low transmit power regime, an algorithm which achieves the maximum spectral efficiency may also achieve the maximum energy efficiency; (2) a high spectral efficiency does not necessarily result in a high energy efficiency; (3) spectral efficiency is always limited by the backhaul capacity; (4) energy efficiency increases with the backhaul capacity only until the maximum energy efficiency is achieved. © 2002-2012 IEEE. Source

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