THESIS
2016
xv, 119 pages : illustrations ; 30 cm
Abstract
Over the past several decades, wireless communications have rapidly expanded, and now
are applied in many aspects of human life. Along with this trend is the growing demand
for higher transmission throughput in the wireless communication scenario. To satisfy this
increasing demand, the concept of cooperative communication has emerged, where users, i.e.,
nodes in a wireless network, help each other by relaying each other's messages to accomplish
the transmission to the destination. The intermediate nodes in a transmission perform as
relays, and different relaying strategies have been proposed with the goal being mitigating the
interference and improving the throughput. Being a type of physical layer network coding,
the compute-and-forward (CF) relaying strategy offers higher tran...[
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Over the past several decades, wireless communications have rapidly expanded, and now
are applied in many aspects of human life. Along with this trend is the growing demand
for higher transmission throughput in the wireless communication scenario. To satisfy this
increasing demand, the concept of cooperative communication has emerged, where users, i.e.,
nodes in a wireless network, help each other by relaying each other's messages to accomplish
the transmission to the destination. The intermediate nodes in a transmission perform as
relays, and different relaying strategies have been proposed with the goal being mitigating the
interference and improving the throughput. Being a type of physical layer network coding,
the compute-and-forward (CF) relaying strategy offers higher transmission rate than the
traditional relaying strategies like amplify-and-forward, compress-and-forward, and decode-and-forward. The achievable transmission rate of a wireless relay network adopting the CF
scheme depends on the network coding (NC) coefficient vectors. However, searching for
optimal NC coefficient vectors turns out to be a combination of multiple shortest vector
problems (SVP) in a lattice. The classical SVP in its general form is very likely NP-hard
and its intractability forms the foundation of lattice-based cryptography.
When there is no feedback from the destination, it is reasonable that each relay chooses the NC coefficient vector that maximizes its computation rate. For the case where feedback
from the destination is available, based on certain low overhead feedback protocol, the CF
design problem can be converted to the problem of finding a list of short NC coefficient
vectors that provide the best computation rate at a single relay. Therefore, solving the SVP
involved is essential to the CF protocol design and the problem has attracted much research
attention. In this thesis, we mainly focus on developing efficient and effective algorithms for
solving the SVP in CF, i.e., searching the best NC coefficient vector that provides the highest
computation rate at a single relay. Three methods are proposed:
1. a low-complexity method based on quadratic programming relaxation that gives a sub-optimal
solution,
2. an efficient method based on the sphere decoding idea and the Schnorr-Euchner search
that gives the optimal solution, and
3. a low-complexity method based on line quantization search that also gives the optimal
solution.
We investigate the efficiency and effectiveness of the proposed methods with both theoretical
analysis and numerical simulations.
Besides developing algorithms for solving the SVP in CF, we also consider the applications
of the developed algorithms in CF design. We first investigate different relay cooperation
strategies in choosing the NC coefficient vectors, which perform differently in terms of the
system transmission rate and the communication overhead. Then we propose a new low
communication overhead strategy and compare it with the two existing strategies. The
previously developed algorithms, with slight modifications, can be applied at the relays to
find a set of best NC coefficient vectors.
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