Cognitive beamforming transmission and energy harvesting with limited primary cooperation: analysis and design
Cognitive radio improves radio spectrum utilization either by spectrum sharing or by opportunistically utilizing the spectrum of the licensed users. Cognitive beam- forming is a prominent technique that can further enhance the overall performance of the wireless communication systems through beam...
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| Format: | Others |
| Language: | English en |
| Published: |
2017
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| Online Access: | https://dspace.library.uvic.ca//handle/1828/8633 |
| Summary: | Cognitive radio improves radio spectrum utilization either by spectrum sharing
or by opportunistically utilizing the spectrum of the licensed users. Cognitive beam-
forming is a prominent technique that can further enhance the overall performance
of the wireless communication systems through beamforming vector design and/or
power allocation. Harvesting radio frequency (RF) energy from existing wireless
communication systems is a promising potential solution for providing convenient,
perpetual and green energy supply to wireless sensor networks (WSN). The amount
of energy that can be harvested from existing RF energy sources over a short period of time can only support low data rate applications with simply transmission strategies. The main challenge for satisfying the energy requirement of WSN is the time-varying wireless fading channels. Low complexity cooperation between WSN and RF energy source can effectively enhance the stability of energy supply for the sensor node. While multiple transmission antennas are deployed at the existing RF energy source, judicious transmit beam selection can further improve the harvested energy at the sensor node, while simultaneously serving multiple users.
In this doctoral research, we present random unitary beamforming (RUB) cooperative beam selection schemes to ensure the QoS of primary system and reduce the
hardware and software complexities of secondary system. We analyze the exact out-
age performance of the primary system, and investigate the tradeoff between primary
system outage probability versus secondary system sum-rate performance. We also
study the performance of overlaid wireless sensor transmission powered by RF energy
harvested from existing wireless system. We derive the exact distribution function of
harvested energy over a certain number channel coherence time over Rayleigh fading
channels with the consideration of hardware limitation, such as energy harvesting
sensitivity and harvesting efficiency. We also analyze the average packet delay and
packet loss probability of sensor transmission subject to interference from existing
system, for both delay insensitive traffics and delay sensitive traffics. The optimal
design of energy storage capacity of the sensor nodes is proposed to minimize the
average packet transmission delay for delay insensitive traffics with two candidate
transmission strategies. We further investigate the energy harvesting performance of
a wireless sensor node powered by RF energy from an existing multiuser MIMO system. Specifically, we propose based cooperative beam selection schemes to enhance
the energy harvesting performance at the sensor. We derive the exact distribution
function of harvested energy in a coherence time and further investigate the performance tradeoff of the average harvested energy at the sensor versus the sum-rate of the multiuser MIMO system. === Graduate |
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