62 research outputs found
Energy efficiency and interference management in long term evolution-advanced networks.
Doctoral Degree. University of KwaZulu-Natal, Durban.Cellular networks are continuously undergoing fast extraordinary evolution to overcome
technological challenges. The fourth generation (4G) or Long Term Evolution-Advanced
(LTE-Advanced) networks offer improvements in performance through increase in network density,
while allowing self-organisation and self-healing. The LTE-Advanced architecture is heterogeneous,
consisting of different radio access technologies (RATs), such as macrocell, smallcells, cooperative
relay nodes (RNs), having various capabilities, and coexisting in the same geographical coverage
area. These network improvements come with different challenges that affect users’ quality of
service (QoS) and network performance. These challenges include; interference management, high
energy consumption and poor coverage of marginal users. Hence, developing mitigation schemes for
these identified challenges is the focus of this thesis.
The exponential growth of mobile broadband data usage and poor networks’ performance along
the cell edges, result in a large increase of the energy consumption for both base stations (BSs) and
users. This due to improper RN placement or deployment that creates severe inter-cell and intracell
interferences in the networks. It is therefore, necessary to investigate appropriate RN placement
techniques which offer efficient coverage extension while reducing energy consumption and mitigating
interference in LTE-Advanced femtocell networks. This work proposes energy efficient and optimal
RN placement (EEORNP) algorithm based on greedy algorithm to assure improved and effective
coverage extension. The performance of the proposed algorithm is investigated in terms of coverage
percentage and number of RN needed to cover marginalised users and found to outperform other RN
placement schemes.
Transceiver design has gained importance as one of the effective tools of interference
management. Centralised transceiver design techniques have been used to improve network
performance for LTE-Advanced networks in terms of mean square error (MSE), bit error rate (BER)
and sum-rate. The centralised transceiver design techniques are not effective and computationally
feasible for distributed cooperative heterogeneous networks, the systems considered in this thesis.
This work proposes decentralised transceivers design based on the least-square (LS) and minimum MSE (MMSE) pilot-aided channel estimations for interference management in uplink
LTE-Advanced femtocell networks. The decentralised transceiver algorithms are designed for the
femtocells, the macrocell user equipments (MUEs), RNs and the cell edge macrocell UEs (CUEs) in
the half-duplex cooperative relaying systems. The BER performances of the proposed algorithms
with the effect of channel estimation are investigated.
Finally, the EE optimisation is investigated in half-duplex multi-user multiple-input
multiple-output (MU-MIMO) relay systems. The EE optimisation is divided into sub-optimal EE
problems due to the distributed architecture of the MU-MIMO relay systems. The decentralised
approach is employed to design the transceivers such as MUEs, CUEs, RN and femtocells for the
different sub-optimal EE problems. The EE objective functions are formulated as convex
optimisation problems subject to the QoS and transmit powers constraints in case of perfect channel
state information (CSI). The non-convexity of the formulated EE optimisation problems is
surmounted by introducing the EE parameter substractive function into each proposed algorithms.
These EE parameters are updated using the Dinkelbach’s algorithm. The EE optimisation of the
proposed algorithms is achieved after finding the optimal transceivers where the unknown
interference terms in the transmit signals are designed with the zero-forcing (ZF) assumption and
estimation errors are added to improve the EE performances. With the aid of simulation results, the
performance of the proposed decentralised schemes are derived in terms of average EE evaluation
and found to be better than existing algorithms
Multipath Parameter Estimation from OFDM Signals in Mobile Channels
We study multipath parameter estimation from orthogonal frequency division
multiplex signals transmitted over doubly dispersive mobile radio channels. We
are interested in cases where the transmission is long enough to suffer time
selectivity, but short enough such that the time variation can be accurately
modeled as depending only on per-tap linear phase variations due to Doppler
effects. We therefore concentrate on the estimation of the complex gain, delay
and Doppler offset of each tap of the multipath channel impulse response. We
show that the frequency domain channel coefficients for an entire packet can be
expressed as the superimposition of two-dimensional complex sinusoids. The
maximum likelihood estimate requires solution of a multidimensional non-linear
least squares problem, which is computationally infeasible in practice. We
therefore propose a low complexity suboptimal solution based on iterative
successive and parallel cancellation. First, initial delay/Doppler estimates
are obtained via successive cancellation. These estimates are then refined
using an iterative parallel cancellation procedure. We demonstrate via Monte
Carlo simulations that the root mean squared error statistics of our estimator
are very close to the Cramer-Rao lower bound of a single two-dimensional
sinusoid in Gaussian noise.Comment: Submitted to IEEE Transactions on Wireless Communications (26 pages,
9 figures and 3 tables
Interference modelling and management for cognitive radio networks
Radio spectrum is becoming increasingly scarce as more and more devices go wireless.
Meanwhile, studies indicate that the assigned spectrum is not fully utilised.
Cognitive radio (CR) technology is envisioned to be a promising solution to address
the imbalance between spectrum scarcity and spectrum underutilisation. It improves
the spectrum utilisation by reusing the unused or underutilised spectrum owned by
incumbent systems (primary systems). With the introduction of CR networks, two
types of interference originating from CR networks are introduced. They are the interference
from CR to primary networks (CR-primary interference) and the interference
among spectrum-sharing CR nodes (CR-CR interference). The interference should be
well controlled and managed in order not to jeopardise the operation of the primary
network and to improve the performance of CR systems. This thesis investigates the
interference in CR networks by modelling and mitigating the CR-primary interference
and analysing the CR-CR interference channels.
Firstly, the CR-primary interference is modelled for multiple CR nodes sharing the
spectrum with the primary system. The probability density functions of CR-primary
interference are derived for CR networks adopting different interference management
schemes. The relationship between CR operating parameters and the resulting CRprimary
interference is investigated. It sheds light on the deployment of CR networks
to better protect the primary system.
Secondly, various interference mitigation techniques that are applicable to CR networks
are reviewed. Two novel precoding schemes for CR multiple-input multipleoutput
(MIMO) systems are proposed to mitigate the CR-primary interference and
maximise the CR throughput. To further reduce the CR-primary interference, we also
approach interference mitigation from a cross-layer perspective by jointly considering
channel allocation in the media access control layer and precoding in the physical
layer of CR MIMO systems.
Finally, we analyse the underlying interference channels among spectrum-sharing CR
users when they interfere with each other. The Pareto rate region for multi-user MIMO
interference systems is characterised. Various rate region convexification schemes are
examined to convexify the rate region. Then, game theory is applied to the interference
system to coordinate the operation of each CR user. Nash bargaining over MIMO
interference systems is characterised as well.
The research presented in this thesis reveals the impact of CR operation on the resulting
CR-primary network, how to mitigate the CR-primary interference and how
to coordinate the spectrum-sharing CR users. It forms the fundamental basis for interference
management in CR systems and consequently gives insights into the design
and deployment of CR networks
Fast converging robust beamforming for downlink massive MIMO systems in heterogenous networks
Massive multiple-input multiple-output (MIMO) is an emerging technology, which is an enabler for future broadband wireless networks that support high speed connection of densely populated areas. Application of massive MIMO at the macrocell base stations in heterogeneous networks (HetNets) offers an increase in throughput without increasing the bandwidth, but with reduced power consumption. This research investigated the optimisation problem of signal-to-interference-plus-noise ratio (SINR) balancing for macrocell users in a typical HetNet scenario with massive MIMO at the base station. The aim was to present an efficient beamforming solution that would enhance inter-tier interference mitigation in heterogeneous networks. The system model considered the case of perfect channel state information (CSI) acquisition at the transmitter, as well as the case of imperfect CSI at the transmitter. A fast converging beamforming solution, which is applicable to both channel models, is presented. The proposed beamforming solution method applies the matrix stuffing technique and the alternative direction method of multipliers, in a two-stage fashion, to give a modestly accurate and efficient solution. In the first stage, the original optimisation problem is transformed into standard second-order conic program (SOCP) form using the Smith form reformulation and applying the matrix stuffing technique for fast transformation. The second stage uses the alternative direction method of multipliers to solve the SOCP-based optimisation problem. Simulations to evaluate the SINR performance of the proposed solution method were carried out with supporting software-based simulations using relevant MATLAB toolboxes. The simulation results of a typical single cell in a HetNet show that the proposed solution gives performance with modest accuracy, while converging in an efficient manner, compared to optimal solutions achieved by state-of-the-art modelling languages and interior-point solvers. This is particularly for cases when the number of antennas at the base station increases to large values, for both models of perfect CSI and imperfect CSI. This makes the solution method attractive for practical implementation in heterogeneous networks with large scale antenna arrays at the macrocell base station.Dissertation (MEng)--University of Pretoria, 2018.Electrical, Electronic and Computer EngineeringMEngUnrestricte
NON-ORTHOGONAL MULTIPLE ACCESS: A COMPREHENSIVE ANALYTICAL STUDY AND OPTIMISATION IN FADING CHANNELS
Power Allocation for Uplink Communications of Massive Cellular-Connected UAVs
Cellular-connected unmanned aerial vehicle (UAV) has attracted a surge of research interest in both academia and industry. To support aerial user equipment (UEs) in the existing cellular networks, one promising approach is to assign a portion of the system bandwidth exclusively to the UAV-UEs. This is especially favorable for use cases where a large number of UAV-UEs are exploited, e.g., for package delivery close to a warehouse. Although the nearly line-of-sight (LoS) channels can result in higher powers received, UAVs can in turn cause severe interference to each other in the same frequency band. In this contribution, we focus on the uplink communications of massive cellular-connected UAVs. Different power allocation algorithms are proposed to either maximize the minimal spectrum efficiency (SE) or maximize the overall SE to cope with severe interference based on the successive convex approximation (SCA) principle. One of the challenges is that a UAV can affect a large area meaning that many more UAV-UEs must be considered in the optimization problem, which is essentially different from that for terrestrial UEs. The necessity of single-carrier uplink transmission further complicates the problem. Nevertheless, we find that the special property of large coherent bandwidths and coherent times of the propagation channels can be leveraged. The performances of the proposed algorithms are evaluated via extensive simulations in the full-buffer transmission mode and bursty-traffic mode. Results show that the proposed algorithms can effectively enhance the uplink SEs. This work can be considered the first attempt to deal with the interference among massive cellular-connected UAV-UEs with optimized power allocations
Power Allocation for Uplink Communications of Massive Cellular-Connected UAVs
Cellular-connected unmanned aerial vehicle (UAV) has attracted a surge of research interest in both academia and industry. To support aerial user equipment (UEs) in the existing cellular networks, one promising approach is to assign a portion of the system bandwidth exclusively to the UAV-UEs. This is especially favorable for use cases where a large number of UAV-UEs are exploited, e.g., for package delivery close to a warehouse. Although the nearly line-of-sight (LoS) channels can result in higher powers received, UAVs can in turn cause severe interference to each other in the same frequency band. In this contribution, we focus on the uplink communications of massive cellular-connected UAVs. Different power allocation algorithms are proposed to either maximize the minimal spectrum efficiency (SE) or maximize the overall SE to cope with severe interference based on the successive convex approximation (SCA) principle. One of the challenges is that a UAV can affect a large area meaning that many more UAV-UEs must be considered in the optimization problem, which is essentially different from that for terrestrial UEs. The necessity of single-carrier uplink transmission further complicates the problem. Nevertheless, we find that the special property of large coherent bandwidths and coherent times of the propagation channels can be leveraged. The performances of the proposed algorithms are evaluated via extensive simulations in the full-buffer transmission mode and bursty-traffic mode. Results show that the proposed algorithms can effectively enhance the uplink SEs. This work can be considered the first attempt to deal with the interference among massive cellular-connected UAV-UEs with optimized power allocations
LiFi Transceiver Designs for 6G Wireless Networks
Due to the dramatic increase in high data rate services, and in order to meet the demands of the sixth-generation (6G) wireless networks, researchers from both academia and industry have been exploring advanced transmission techniques, new network archi-
tectures and new frequency bands, such as the millimeter wave (mmWave), the infrared, and the visible light bands. Light-fdelity (LiFi) particularly is an emerging, novel, bidirectional, high-speed and fully networked optical wireless communication (OWC) technology that has been introduced as a promising solution for 6G networks, especially for indoor connectivity, owing to the large unexploited spectrum that translates to signifcantly high data rates.
Although there has been a big leap in the maturity of the LiFi technology, there is still a considerable gap between the available LiFi technology and the required demands of 6G networks. Motivated by this, this dissertation aims to bridge between the current research literature of LiFi and the expected demands of 6G networks. Specifcally, the key goal of this dissertation is to fll some shortcomings in the LiFi technology, such as channel modeling, transceiver designs, channel state information (CSI) acquisition, localization, quality-of-service (QoS), and performance optimization. Our work is devoted to address and solve some of these limitations. Towards achieving this goal, this dissertation makes signifcant contributions to several areas of LiFi. First, it develops novel and measurements-based channel models for LiFi systems that are required for performance analysis and handover management. Second, it proposes a novel design for LiFi devices that is capable of alleviating the real behaviour of users and the impurities of indoor
propagation environments. Third, it proposes intelligent, accurate and fast joint position and orientation techniques for LiFi devices, which improve the CSI estimation process and boost the indoor location-based and navigation-based services. Then, it proposes novel proactive optimization technique that can provide near-optimal and real-time service for indoor mobile LiFi users that are running some services with high data rates, such as extended reality, video conferencing, and real-time video monitoring. Finally, it proposes advanced multiple access techniques that are capable of cancelling the efects of interference in indoor multi-user settings. The studied problems are tackled using various tools from probability and statistic theory, system design and integration theory, optimization theory, and deep learning. The Results demonstrate the efectiveness of the proposed designs, solutions, and techniques. Nevertheless, the fndings in this dissertation highlight key guidelines for the efective design of LiFi while considering their unique propagation
features
- …