IX – CICLO DE AUDITORÍA

The focus of this thesis has been on proposing and analyzing signal pro-

cessing algorithms, in particular mathematical optimization techniques, for

the enhancement of coverage and capacity of wireless networks. There are

various techniques that have the potential to enhance capacity and cov-

erage, for example spatial diversity techniques, cognitive radio techniques,

relay networks, heterogenous networks and advanced error control coding

techniques. Among these available techniques, the spatial diversity and cog-

nitive radio techniques have the ability to enhance the usage of the spectrum

and to increase the capacity substantially. Relay technology has the abil-

ity to enhance the coverage and also to minimize the power consumption for

transmission of signals in the network. The emphasize on the work presented

in this thesis has been on spatial diversity techniques and relay network as

well as cognitive radio technology. In particular, various mathematical opti-

mization techniques have been proposed for optimal resource allocation and

Section 7.1. Summary and Conclusions 164

spatial diversity for wireless relay networks. The work also considered de-

signing such systems under interference constraints, so that is applicable to

cognitive radio networks as well. Having designed various relay networking

technologies, the final part of the thesis focused on coordinated multi-cell

processing, in particular coordinated beamformer design for enhancing ca-

pacity.

The first contributing chapter “Wireless Peer-to-Peer Relay Networks”

had four contributions on peer-to-peer wireless networks. There have been

various works available in the literature on designing wireless relay networks

to achieve a certain QoS. However the work considered in this thesis fo-

cused on designing wireless relay networks while ensuring users’ fairness in

the form of maximizing the worst case user SINR in the network. This is

termed as SINR balancing. The work considered both one way and two

way relay networks with and without consideration to interference leakage

to primary users as in a cognitive radio network. Accordingly, the work

considered multiple peer-to-peer users and a number of spatially distributed

relays. The aim of the relay is to receive the signal from multiple users,

amplify and rotate the phase and forward them to the destinations. In that

process, the relay is expected to perform spatial diversity, as the aim is to

maximize the worst case SINR of the users at the destination. This problem

was solved using a combination of SDP and GP and the simulation results

shown multiple spatially distributed relays have the ability to perform spatial

multiplexing and forward the signal to the destination, even in the presence

of multiple users and even if the relays have only one antenna. This work

has been extended to two-way relay networks as well. Finally the work has

been extended to a CR network, where the aim of the relay is not only to

perform spatial multiplexing and to forward the signal to the destination,

however the relay should also need to ensure the interference leakage to a

Section 7.1. Summary and Conclusions 165

In the second contributing chapter, we extended the peer-to-peer wire-

less relay network to a relay that consists of multiple antennas and the peer

to peer users have multiple antennas at both the transmitting and the re-

ceiving end. Hence, we used MMSE as the criterion for optimization. The

aim of the MIMO relay as well as the transceivers of the peer-to-peer users

is to minimize the weighted sum MMSE of the network for a given total

network power. This problem has been solved using uplink-downlink du-

ality and SOCP. According to the uplink-downlink duality, the receiver is

fixed and the transmitter is designed by converting the problem into a vir-

tual uplink problem. Once the transmitter has been designed, it is fixed

and the receivers are designed directly using MMSE technique. The op-

timum relay transceiver matrix has been designed using SOCP. Hence an

iterative method was proposed. It is understood that the overall problem

is not convex, however this iterative method has provided reasonably good

performance for a variety of random channels.

The third contributing chapter focused again on relay network problem.

Specifically a BS with multiple antennas serving a number of users directly

and another set of users through a MIMO relay has been considered. The

aim is to jointly design the beamformers required at the BS and at the re-

lay to ensure that the users served by both the BS and the relay achieve a

set of target SINRs (for a given transmission power at the BS and at the

relay). According to this setup, for each complete transmission, there are

two time slots. In the first time slot, the BS sends information to the users

that serves directly and to the relay. In the second time slot, both the BS

and the relay transmit signal to their corresponding users. The signal that

needs to be transmitted to the corresponding users of the relay, has been

transmitted by the BS during the first time slot. The work available in the

literature, considered the signal received by the users in the second time slot

Section 7.1. Summary and Conclusions 166

as this is the very same signal that has been transmitted by the BS in the

first time slot, it should not be considered as interference, as the interference

structure is already known at the BS. This concept has been exploited and

a novel technique has been proposed. The BS in the second time slot not

only designs beamformer to send information to the users it serves, however

also to mitigate interference caused by the relay as the BS knows the exact

interference structure. This technique has been shown to outperform other

techniques available in the literature.

Final contributing chapter has been on multi-cell beamforming. Tradi-

tionally, spatial diversity or beamforming techniques, have been designed

for each BS considering the interference from other BSs as noise. However,

coordinated multi-cell processing aims to design beamformers jointly for a

set of BSs. There are various beamforming techniques known in the litera-

ture, including designing beamformers to achieve a set of SINR targets for

users served by various BSs and also to maximize the worst case user SINR,

namely SINR balancing. However, all the techniques available in the lit-

erature on SINR balancing based beamformer design aimed to balance the

SINR of all users in all cells together. This is however, not desirable, because

users that are in a BS with good channel conditions or higher transmission

power may be disadvantaged as the balanced overall SINR values are limited

by the worst case user in the worst case BS. Therefore, a new approach has

been proposed that aims to balance SINR of users in various cells to various

levels. This has been solved using an SINR target based SINR balancing

technique. The results have been proved to be optimal using a set of simu-

lation results that compares the performance with that obtained using SDP

techniques.

In summary this thesis has investigated various spatial diversity tech-

niques and resource allocation techniques for enhancing the capacity and

Section 7.2. Future Work 167

uplink-downlink duality and convex optimization techniques, in particular

SDP, SOCP and GP.