Call admission control using cell breathing concept for wideband CDMA

This paper presents a Call Admission Control (CAC) algorithm based fuzzy logic to maintain the quality of service using cell breathing concept. When a new call is accepted by a cell, its current user is generally affected due to cell breathing. The proposed CAC algorithm accepts a new call only if the current users in the cell are not jeopardized. Performance evaluation is done for single-cell and multicell scenarios. In multicell scenario dynamic assignment of users to the neighboring cell, so called handoff, has been considered to achieve a lower blocking probability. Handoff and new call requests are assumed with handoff being given preference using a reserved channel scheme. CAC for different types of services are shown which depend upon the bandwidth requirement for voice, data and video. Distance, arrival rate, bandwidth and nonorthogonality factor of the signal are considered for making the call acceptance decision. The paper demonstrates that fuzzy logic with the cell breathing concept can be used to develop a CAC algorithm to achieve a better performance evaluation

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

Energy Efficient Cloud Computing Based Radio Access Networks in 5G. Design and evaluation of an energy aware 5G cloud radio access networks framework using base station sleeping, cloud computing based workload consolidation and mobile edge computing

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increase energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices cause a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS

Interference Aware Cognitive Femtocell Networks

Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks. Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision. This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference

Quality of service differentiation for multimedia delivery in wireless LANs

Delivering multimedia content to heterogeneous devices over a variable networking environment while maintaining high quality levels involves many technical challenges. The research reported in this thesis presents a solution for Quality of Service (QoS)-based service differentiation when delivering multimedia content over the wireless LANs. This thesis has three major contributions outlined below: 1. A Model-based Bandwidth Estimation algorithm (MBE), which estimates the available bandwidth based on novel TCP and UDP throughput models over IEEE 802.11 WLANs. MBE has been modelled, implemented, and tested through simulations and real life testing. In comparison with other bandwidth estimation techniques, MBE shows better performance in terms of error rate, overhead, and loss. 2. An intelligent Prioritized Adaptive Scheme (iPAS), which provides QoS service differentiation for multimedia delivery in wireless networks. iPAS assigns dynamic priorities to various streams and determines their bandwidth share by employing a probabilistic approach-which makes use of stereotypes. The total bandwidth to be allocated is estimated using MBE. The priority level of individual stream is variable and dependent on stream-related characteristics and delivery QoS parameters. iPAS can be deployed seamlessly over the original IEEE 802.11 protocols and can be included in the IEEE 802.21 framework in order to optimize the control signal communication. iPAS has been modelled, implemented, and evaluated via simulations. The results demonstrate that iPAS achieves better performance than the equal channel access mechanism over IEEE 802.11 DCF and a service differentiation scheme on top of IEEE 802.11e EDCA, in terms of fairness, throughput, delay, loss, and estimated PSNR. Additionally, both objective and subjective video quality assessment have been performed using a prototype system. 3. A QoS-based Downlink/Uplink Fairness Scheme, which uses the stereotypes-based structure to balance the QoS parameters (i.e. throughput, delay, and loss) between downlink and uplink VoIP traffic. The proposed scheme has been modelled and tested through simulations. The results show that, in comparison with other downlink/uplink fairness-oriented solutions, the proposed scheme performs better in terms of VoIP capacity and fairness level between downlink and uplink traffic

Comprehensive survey on quality of service provisioning approaches in cognitive radio networks : part one

Much interest in Cognitive Radio Networks (CRNs) has been raised recently by enabling unlicensed (secondary) users to utilize the unused portions of the licensed spectrum. CRN utilization of residual spectrum bands of Primary (licensed) Networks (PNs) must avoid harmful interference to the users of PNs and other overlapping CRNs. The coexisting of CRNs depends on four components: Spectrum Sensing, Spectrum Decision, Spectrum Sharing, and Spectrum Mobility. Various approaches have been proposed to improve Quality of Service (QoS) provisioning in CRNs within fluctuating spectrum availability. However, CRN implementation poses many technical challenges due to a sporadic usage of licensed spectrum bands, which will be increased after deploying CRNs. Unlike traditional surveys of CRNs, this paper addresses QoS provisioning approaches of CRN components and provides an up-to-date comprehensive survey of the recent improvement in these approaches. Major features of the open research challenges of each approach are investigated. Due to the extensive nature of the topic, this paper is the first part of the survey which investigates QoS approaches on spectrum sensing and decision components respectively. The remaining approaches of spectrum sharing and mobility components will be investigated in the next part

Load balancing in hybrid LiFi and RF networks

The increasing number of mobile devices challenges the current radio frequency (RF) networks. The conventional RF spectrum for wireless communications is saturating, motivating to develop other unexplored frequency bands. Light Fidelity (LiFi) which uses more than 300 THz of the visible light spectrum for high-speed wireless communications, is considered a promising complementary technology to its RF counterpart. LiFi enables daily lighting infrastructures, i.e. light emitting diode (LED) lamps to realise data transmission, and maintains the lighting functionality at the same time. Since LiFi mainly relies on line-of-sight (LoS) transmission, users in indoor environments may experience blockages which significantly affects users’ quality of service (QoS). Therefore, hybrid LiFi and RF networks (HLRNs) where LiFi supports high data rate transmission and RF offers reliable connectivity, can provide a potential solution to future indoor wireless communications. In HLRNs, efficient load balancing (LB) schemes are critical in improving the traffic performance and network utilisation. In this thesis, the optimisation-based scheme (OBS) and the evolutionary game theory (EGT) based scheme (EGTBS) are proposed for load balancing in HLRNs. Specifically, in OBS, two algorithms, the joint optimisation algorithm (JOA) and the separate optimisation algorithm (SOA) are proposed. Analysis and simulation results show that JOA can achieve the optimal performance in terms of user data rate while requiring high computational complexity. SOA reduces the computational complexity but achieves low user data rates. EGTBS is able to achieve a better performance/complexity trade-off than OBS and other conventional load balancing schemes. In addition, the effects of handover, blockages, orientation of LiFi receivers, and user data rate requirement on the throughput of HLRNs are investigated. Moreover, the packet latency in HLRNs is also studied in this thesis. The notion of LiFi service ratio is introduced, defined as the proportion of users served by LiFi in HLRNs. The optimal LiFi service ratio to minimise system delay is mathematically derived and a low-complexity packet flow assignment scheme based on this optimum ratio is proposed. Simulation results show that the theoretical optimum of the LiFi service ratio is very close to the practical solution. Also, the proposed packet flow assignment scheme can reduce at most 90% of packet delay compared to the conventional load balancing schemes at reduced computational complexity

Call admission control for interactive multimedia satellite networks.

Master of Science in Engineering (Electronic). University of KwaZulu-Natal, Durban 2015.Satellite communication has become an integral component of global access communication network due mainly to its ubiquitous coverage, large bandwidth and ability to support for large numbers of users over fixed and mobile devices. However, the multiplicity of multimedia applications with diverse requirements in terms of quality of service (QoS) poses new challenges in managing the limited and expensive resources. Furthermore, the time-varying nature of the propagation channel due to atmospheric and environmental effects also poses great challenges to effective utilization of resources and the satisfaction of users’ QoS requirements. Efficient radio resource management (RRM) techniques such as call admission control (CAC) and adaptive modulation and coding (AMC) are required in order to guarantee QoS satisfaction for user established connections and realize maximum and efficient utilization of network resources. In this work, we propose two CAC policies for interactive satellite multimedia networks. The two policies are based on efficient adaptation of transmission parameters to the dynamic link characteristics. In the first policy which we refer to as Gaussian Call Admission Control with Link Adaptation (GCAC-LA), we invoke the central limit theorem to statistically multiplex rate based dynamic capacity (RBDC) connections and obtain an aggregate bandwidth and required capacity for the multiplex. Adaptive Modulation and Coding (AMC) is employed for transmission over the time-varying wireless channel of the return link of an interactive satellite network. By associating users’ channel states to particular transmission parameters, the amount of resources required to satisfy user connection requirements in each state is determined. Thus the admission control policy considers in its decision, the channel states of all existing and new connections. The performance of the system is investigated by simulation and the results show that AMC significantly improves the utilization and call blocking performance by more than twice that of a system without link adaptation. In the second policy, a Game Theory based CAC policy with link adaptation (GTCAC-LA) is proposed. The admission of a new user connection under the GTCAC-LA policy is based on a non-cooperative game that is played between the network (existing user connections) and the new connection. A channel prediction scheme that predicts the rain attenuation on the link in successive intervals of time is also proposed. This determines the current resource allocation for every source at any point in time. The proposed game is played each time a new connection arrives and the strategies adopted by players are based on utility function, which is estimated based on the required capacity and the actual resources allocated. The performance of the CAC policy is investigated for different prediction intervals and the results show that multiple interval prediction scheme shows better performance than the single interval scheme. Performance of the proposed CAC policies indicates their suitability for QoS provisioning for traffic of multimedia connections in future 5G networks