How to Solve the Fronthaul Traffic Congestion Problem in H-CRAN?

The design of efficient wireless fronthaul connections for future heterogeneous networks incorporating emerging paradigms such as heterogeneous cloud radio access network (H-CRAN) has become a challenging task that requires the most effective utilization of fronthaul network resources. In this paper, we propose and analyze possible solutions to facilitate the fronthaul traffic congestion in the scenario of Coordinated Multi-Point (CoMP) for 5G cellular traffic which is expected to reach ZetaByte by 2017. In particular, we propose to use distributed compression to reduce the fronthaul traffic for H-CRAN. Unlike the conventional approach where each coordinating point quantizes and forwards its own observation to the processing centre, these observations are compressed before forwarding. At the processing centre, the decompression of the observations and the decoding of the user messages are conducted in a joint manner. Our results reveal that, in both dense and ultra-dense urban small cell deployment scenarios, the usage of distributed compression can efficiently reduce the required fronthaul rate by more than 50% via joint operation

Interference cancellation and Resource Allocation approaches for Device-to-Device Communications

Network assisted Device-to-Device (D2D) communication as an underlay to cellular spectrum has attracted much attention in mobile network standards for local area connectivity as a means to improve the cellular spectrum utilization and to reduce the energy consumption of User Equipments (UEs). The D2D communication uses resources of the underlying mobile network which results in different interference scenarios. These include interference from cellular to D2D link, D2D to cellular link and interference among D2D links when multiple D2D links share common resources. In this thesis, an orthogonal precoding interference cancellation method is initially presented to reduce the cellular to D2D and D2D to cellular interferences when the cellular channel resources are being shared by a single D2D link. Three different scenarios have been considered when establishing a D2D communication along with a Base Station-to-UE communication. The proposed method is analytically evaluated in comparison with the conventional precoding matrix allocation method in terms of ergodic capacity. This method is then extended for a cluster based multi-link D2D scenario where interference between D2D pairs also exists in addition to the other two interference scenarios. In this work, cluster denotes a group of devices locally communicating through multi-link D2D communications sharing the same radio resources of the Cluster Head. Performance of the proposed method is evaluated and compared for different resource sharing modes. The analyses illustrate the importance of cluster head in each cluster to save the battery life of devices in that cluster. The outage probability is considered as a performance evaluation matrix for guaranteeing QoS constrain of communication links. Hence, the mathematical expressions for outage probability of the proposed method for single-link and multi-link D2D communications are presented and compared with an existing interference cancellation technique. To execute the cluster based interference cancellation approach, a three-step resource allocation scheme is then proposed. It first performs a mode selection procedure to choose the transmission mode of each UEs. Then a clustering scheme is developed to group the links that can share a common resource to improve the spectral efficiency. For the selection of suitable cellular UEs for each cluster whose resource can be shared, a cluster head selection algorithm is also developed. Maximal residual energy and minimal transmit power have been considered as parameters for the cluster head selection scheme. Finally, the expression for maximum number of links that the radio resource of shared UE can support is analytically derived. The performance of the proposed scheme is evaluated using a WINNER II A1 indoor office model. The performance of D2D communication practically gets limited due to large distance and/or poor channel conditions between the D2D transmitter and receiver. To overcome these issues, a relay-assisted D2D communication is introduced in this thesis where a device relaying is an additional transmission mode along with the existing cellular and D2D transmission modes. A transmission mode assignment algorithm based on the Hungarian algorithm is then proposed to improve the overall system throughput. The proposed algorithm tries to solve two problems: a suitable transmission mode selection for each scheduled transmissions and a device selection for relaying communication between user equipments in the relay transmission mode. Simulation results showed that our proposed algorithm improves the system performance in terms of the overall system throughput and D2D data rate in comparison with traditional D2D communication schemes

System capacity enhancement for 5G network and beyond

A thesis submitted to the University of Bedfordshire, in fulfilment of the requirements for the degree of Doctor of PhilosophyThe demand for wireless digital data is dramatically increasing year over year. Wireless communication systems like Laptops, Smart phones, Tablets, Smart watch, Virtual Reality devices and so on are becoming an important part of people’s daily life. The number of mobile devices is increasing at a very fast speed as well as the requirements for mobile devices such as super high-resolution image/video, fast download speed, very short latency and high reliability, which raise challenges to the existing wireless communication networks. Unlike the previous four generation communication networks, the fifth-generation (5G) wireless communication network includes many technologies such as millimetre-wave communication, massive multiple-input multiple-output (MIMO), visual light communication (VLC), heterogeneous network (HetNet) and so forth. Although 5G has not been standardised yet, these above technologies have been studied in both academia and industry and the goal of the research is to enhance and improve the system capacity for 5G networks and beyond by studying some key problems and providing some effective solutions existing in the above technologies from system implementation and hardware impairments’ perspective. The key problems studied in this thesis include interference cancellation in HetNet, impairments calibration for massive MIMO, channel state estimation for VLC, and low latency parallel Turbo decoding technique. Firstly, inter-cell interference in HetNet is studied and a cell specific reference signal (CRS) interference cancellation method is proposed to mitigate the performance degrade in enhanced inter-cell interference coordination (eICIC). This method takes carrier frequency offset (CFO) and timing offset (TO) of the user’s received signal into account. By reconstructing the interfering signal and cancelling it afterwards, the capacity of HetNet is enhanced. Secondly, for massive MIMO systems, the radio frequency (RF) impairments of the hardware will degrade the beamforming performance. When operated in time duplex division (TDD) mode, a massive MIMO system relies on the reciprocity of the channel which can be broken by the transmitter and receiver RF impairments. Impairments calibration has been studied and a closed-loop reciprocity calibration method is proposed in this thesis. A test device (TD) is introduced in this calibration method that can estimate the transmitters’ impairments over-the-air and feed the results back to the base station via the Internet. The uplink pilots sent by the TD can assist the BS receivers’ impairment estimation. With both the uplink and downlink impairments estimates, the reciprocity calibration coefficients can be obtained. By computer simulation and lab experiment, the performance of the proposed method is evaluated. Channel coding is an essential part of a wireless communication system which helps fight with noise and get correct information delivery. Turbo codes is one of the most reliable codes that has been used in many standards such as WiMAX and LTE. However, the decoding process of turbo codes is time-consuming and the decoding latency should be improved to meet the requirement of the future network. A reverse interleave address generator is proposed that can reduce the decoding time and a low latency parallel turbo decoder has been implemented on a FPGA platform. The simulation and experiment results prove the effectiveness of the address generator and show that there is a trade-off between latency and throughput with a limited hardware resource. Apart from the above contributions, this thesis also investigated multi-user precoding for MIMO VLC systems. As a green and secure technology, VLC is achieving more and more attention and could become a part of 5G network especially for indoor communication. For indoor scenario, the MIMO VLC channel could be easily ill-conditioned. Hence, it is important to study the impact of the channel state to the precoding performance. A channel state estimation method is proposed based on the signal to interference noise ratio (SINR) of the users’ received signal. Simulation results show that it can enhance the capacity of the indoor MIMO VLC system

Joint routing and resource allocation for wireless backhauling of small cell networks

The future communication networks are destined to support an increasingly large amount of data traffic, and for that reason, efficient mechanisms to manage them are necessary. Based on a backhaul network, and starting from specific scenarios, we develop methods to jointly optimize the routing parameters and resources of this network. We relate this optimization with the Software Defined Networks and network virtualization concepts, which allow us to have an overall vision of the network, and lead us to study its decomposition. To do this, we use convex optimization techniques, which have very efficient resolution mechanisms, and help us to obtain tools for interpreting the obtained results and perform analysis on the network parameters. The achieved results show a great improvement in relation to the non-optimized case in terms of carried traffic, which is an assessment we make in the final economic analysis.Las redes de comunicaciones del futuro están destinadas a soportar una cantidad de tráfico de datos cada vez más elevada, y por eso son necesarios mecanismos eficientes para gestionarlas. Basándonos en una red de backhaul y partiendo de escenarios concretos, desarrollamos métodos para optimizar conjuntamente los parámetros de enrutamiento y los recursos de esta red. Esta optimización la ligamos con los conceptos de Software Defined Networksk y de network virtualization, que nos permiten tener una visión general de la red, y nos conducen a estudiar su descomposición. Esto lo hacemos usando técnicas de optimización convexa, que tiene mecanismos de resolución muy eficientes, y nos ayuda a obtener herramientas para interpretar los resultados obtenidos y hacer análisis de los parámetros de la red. Los resultados conseguidos muestran una gran mejora con relación al caso no optimizado en términos de tráfico transportado, valoración que recogemos en un análisis económico final.Les xarxes de comunicacions del futur estan destinades a suportar una quantitat de trànsit de dades cada cop més elevada, i per això són necessaris mecanismes eficients per a gestionar-les. Basant-nos en una xarxa de backhaul i partint d?escenaris concrets, desenvolupem mètodes per a optimitzar conjuntament els paràmetres d?encaminament i els recursos d?aquesta xarxa. Aquesta optimització la lliguem amb els conceptes de Software Defined Network i de network virtualization, que ens permeten tenir una visió general de la xarxa, i ens condueixen a estudiar-ne la seva descomposició. Tot això ho fem utilitzant tècniques d?optimització convexa, que té mecanismes de resolució molt eficients, i ens ajuda a obtenir eines per a interpretar els resultats obtinguts i fer anàlisis dels punts forts i febles de la xarxa. Els resultats aconseguits mostren una gran millora respecte el cas no optimitzat en termes de trànsit transportat, valoració que recollim en una anàlisi econòmica final

Resource Allocation in Multi-user MIMO Networks: Interference Management and Cooperative Communications

Nowadays, wireless communications are becoming so tightly integrated in our daily lives, especially with the global spread of laptops, tablets and smartphones. This has paved the way to dramatically increasing wireless network dimensions in terms of subscribers and amount of flowing data. Therefore, the two important fundamental requirements for the future 5G wireless networks are abilities to support high data traffic and exceedingly low latency. A likely candidate to fulfill these requirements is multicell multi-user multi-input multiple-output (MU-MIMO); also termed as coordinated multi-point (CoMP) transmission and reception. To achieve the highest possible performance in MU-MIMO networks, a properly designed resource allocation algorithm is needed. Moreover, with the rapidly growing data traffic, interference has become a major limitation in wireless networks. Interference alignment (IA) has been shown to significantly manage the interference and improve the network performance. However, how practically use IA to mitigate interference in a downlink MU-MIMO network still remains an open problem. In this dissertation, we improve the performance of MU-MIMO networks in terms of spectral efficiency, by designing and developing new beamforming algorithms that can efficiently mitigate the interference and allocate the resources. Then we mathematically analyze the performance improvement of MUMIMO networks employing proposed techniques. Fundamental relationships between network parameters and the network performance is revealed, which provide guidance on the wireless networks design. Finally, system level simulations are conducted to investigate the performance of the proposed strategies

Transceiver design and multi-hop D2D for UAV IoT coverage in disasters

When natural disasters strike, the coverage for Internet of Things (IoT) may be severely destroyed, due to the damaged communications infrastructure. Unmanned aerial vehicles (UAVs) can be exploited as flying base stations to provide emergency coverage for IoT, due to its mobility and flexibility. In this paper, we propose multi-antenna transceiver design and multi-hop device-to-device (D2D) communication to guarantee the reliable transmission and extend the UAV coverage for IoT in disasters. Firstly, multi-hop D2D links are established to extend the coverage of UAV emergency networks due to the constrained transmit power of the UAV. In particular, a shortest-path-routing algorithm is proposed to establish the D2D links rapidly with minimum nodes. The closed-form solutions for the number of hops and the outage probability are derived for the uplink and downlink. Secondly, the transceiver designs for the UAV uplink and downlink are studied to optimize the performance of UAV transmission. Due to the non-convexity of the problem, they are first transformed into convex ones and then, low-complexity algorithms are proposed to solve them efficiently. Simulation results show the performance improvement in the throughput and outage probability by the proposed schemes for UAV wireless coverage of IoT in disasters

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