897 research outputs found
Wireless Information and Power Transfer in Full-Duplex Systems with Massive Antenna Arrays
We consider a multiuser wireless system with a full-duplex hybrid access
point (HAP) that transmits to a set of users in the downlink channel, while
receiving data from a set of energy-constrained sensors in the uplink channel.
We assume that the HAP is equipped with a massive antenna array, while all
users and sensor nodes have a single antenna. We adopt a time-switching
protocol where in the first phase, sensors are powered through wireless energy
transfer from HAP and HAP estimates the downlink channel of the users. In the
second phase, sensors use the harvested energy to transmit to the HAP. The
downlink-uplink sum-rate region is obtained by solving downlink sum-rate
maximization problem under a constraint on uplink sum-rate. Moreover, assuming
perfect and imperfect channel state information, we derive expressions for the
achievable uplink and downlink rates in the large-antenna limit and approximate
results that hold for any finite number of antennas. Based on these analytical
results, we obtain the power-scaling law and analyze the effect of the number
of antennas on the cancellation of intra-user interference and the
self-interference.Comment: Accepted for the IEEE International Conference on Communications (ICC
2017
Optimal Multiuser Scheduling Schemes for Simultaneous Wireless Information and Power Transfer
In this paper, we study the downlink multiuser scheduling problem for systems
with simultaneous wireless information and power transfer (SWIPT). We design
optimal scheduling algorithms that maximize the long-term average system
throughput under different fairness requirements, such as proportional fairness
and equal throughput fairness. In particular, the algorithm designs are
formulated as non-convex optimization problems which take into account the
minimum required average sum harvested energy in the system. The problems are
solved by using convex optimization techniques and the proposed optimization
framework reveals the tradeoff between the long-term average system throughput
and the sum harvested energy in multiuser systems with fairness constraints.
Simulation results demonstrate that substantial performance gains can be
achieved by the proposed optimization framework compared to existing suboptimal
scheduling algorithms from the literature.Comment: Accepted for presentation at the European Signal Processing
Conference 201
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