3,542 research outputs found
Physical Layer Service Integration in 5G: Potentials and Challenges
High transmission rate and secure communication have been identified as the
key targets that need to be effectively addressed by fifth generation (5G)
wireless systems. In this context, the concept of physical-layer security
becomes attractive, as it can establish perfect security using only the
characteristics of wireless medium. Nonetheless, to further increase the
spectral efficiency, an emerging concept, termed physical-layer service
integration (PHY-SI), has been recognized as an effective means. Its basic idea
is to combine multiple coexisting services, i.e., multicast/broadcast service
and confidential service, into one integral service for one-time transmission
at the transmitter side. This article first provides a tutorial on typical
PHY-SI models. Furthermore, we propose some state-of-the-art solutions to
improve the overall performance of PHY-SI in certain important communication
scenarios. In particular, we highlight the extension of several concepts
borrowed from conventional single-service communications, such as artificial
noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These
techniques are shown to be effective in the design of reliable and robust
PHY-SI schemes. Finally, several potential research directions are identified
for future work.Comment: 12 pages, 7 figure
Throughput Optimization for Massive MIMO Systems Powered by Wireless Energy Transfer
This paper studies a wireless-energy-transfer (WET) enabled massive
multiple-input-multiple-output (MIMO) system (MM) consisting of a hybrid
data-and-energy access point (H-AP) and multiple single-antenna users. In the
WET-MM system, the H-AP is equipped with a large number of antennas and
functions like a conventional AP in receiving data from users, but additionally
supplies wireless power to the users. We consider frame-based transmissions.
Each frame is divided into three phases: the uplink channel estimation (CE)
phase, the downlink WET phase, as well as the uplink wireless information
transmission (WIT) phase. Firstly, users use a fraction of the previously
harvested energy to send pilots, while the H-AP estimates the uplink channels
and obtains the downlink channels by exploiting channel reciprocity. Next, the
H-AP utilizes the channel estimates just obtained to transfer wireless energy
to all users in the downlink via energy beamforming. Finally, the users use a
portion of the harvested energy to send data to the H-AP simultaneously in the
uplink (reserving some harvested energy for sending pilots in the next frame).
To optimize the throughput and ensure rate fairness, we consider the problem of
maximizing the minimum rate among all users. In the large- regime, we obtain
the asymptotically optimal solutions and some interesting insights for the
optimal design of WET-MM system. We define a metric, namely, the massive MIMO
degree-of-rate-gain (MM-DoRG), as the asymptotic UL rate normalized by
. We show that the proposed WET-MM system is optimal in terms of
MM-DoRG, i.e., it achieves the same MM-DoRG as the case with ideal CE.Comment: 15 double-column pages, 6 figures, 1 table, to appear in IEEE JSAC in
February 2015, special issue on wireless communications powered by energy
harvesting and wireless energy transfe
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