Anwer Al-Dulaimi

5G Communications Race: Pursuit of More Capacity Triggers LTE in Unlicensed Band

Fifth-generation (5G) network developers need to identify the necessary requirements toward additional capacity and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in the Wi-Fi band is motivating operators to combine long-term evolution (LTE) with Wi-Fi technologies. This new LTE in unlicensed band (LTE-U) has the physical layer topology to access Wi-Fi spectrum, specifically the 5-GHz band. Nevertheless, the evolution of LTE-U affects the Wi-Fi operations due to the absence of any regularity for LTE-U transmissions in unlicensed band. In this article, we address the challenges for Wi-Fi to maintain transmissions under the umbrella of LTE-U as Wi-Fi is pushed offline because of the listen-before-talk (LBT) feature. Therefore, we derive a new adaptive LBT mechanism and and virtualized core network for the best practices in both Wi-Fi and LTE-U technologies. The proposed solutions include noncoordinated and coordinated network managements to enable coexistence between both technologies using tradeoff performance for fair spectrum sharing. We concentrate on the initial coexistent technique and discuss how it maps to higher-layer improvements. This article shows new approaches to achieve the Third-Generation Partnership Project (3GPP) Release 13.

Cognitive Mesh Networks

A new subnet, integrating the CR and the fiber-access system, is proposed as cognitive radio-over-fiber (CRoF). The aim of the CRoF system is to serve microcells and to achieve higher throughput and lower time delay in small, cognitive, enterprise broadcasting. The CRoF architecture is based on connecting the core CRoF system at the macrocell BS to the terminals of various microcells using the RoF. The terminals can be short-range transmission stations or just bridges that connect microcells wirelessly to the CRoF headquarters. This article gives a brief description for the future working schemes of each of the proposed CRoF implementation scenarios. Opnet simulations were conducted to evaluate the performance of different CRoF designs in coexistence with the primary network. Results show the dominance of the CRoF implementation using multiple, small, fixed radios,and connected via fiber over all other CRoF designed, and traditional CR management systems. The CRoF system is proposed for future applications in CMNs. Further research is required to analyze the performance of the proposed CRoF management scenarios in green communications.

Cyclostationary Detection of Undefined Secondary Users

Spectrum sensing has continued to emerge as an essential topic for the cognitive networks where two kinds of users primary and secondary will share the band. This paper proposes a method for real-time detection of secondary users at the base stations. Cognitive radios may hide themselves in between the primary users to avoid being charged for using spectrum. To deal with such scenario, a cyclostationary Fast Fourier Transform FFT Accumulation Method (FAM) has been used to develop a new strategy for channel users recognition. Channel users are tracked according to the changes in their signal parameters for instance modulation techniques. The Matlab simulation runs two signals transmitted on 805 MHz channel. Obtained spectral correlation density functions show successful recognition between different signals.

An Intelligent Scheme for First Run Cognitive Radios

Cognitive Radio (CR) can access the spectrum temporarily to solve the problem of the near spectrum crunch. The previous transmissions’ events are one of the main motivations for the CR actions and its learning procedures. Therefore, self aware CR devices may cause a considerable interference when they transmit for the first time with no practical knowledge. This paper proposes a solution for cognitive radios with no experiences for instance first run cognitive radios and CR devices repositioned in new wireless environments. A multi-layered learning system is designed using the neural networks to extract cognition from other operator secondary users. Thus, sensors data, other CR devices’ data, spectrum governing entities behaviour, in addition to any stored data in the CR are processed for decision comparisons. Final evaluations are based on the weight and significance given to each of these inputs. As a result, full autonomous mature cognitive users are created through understanding other cognitive radios experiments. Simulation was trained to assess the proposed learning model. Results show promising and efficient utilization using gradual learning rate algorithms with the designed system.

5G Green Communications: C-RAN Provisioning of CoMP and Femtocells for Power Management

The fifth generation (5G) wireless network is ex- pected to have dense deployments of cells in order to provide efficient Internet and cellular connections. The cloud radio access network (C- RAN) emerges as one of the 5G solutions to steer the network architecture and control resources beyond the legacy radio access technologies. The C-RAN decouples the traffic management operations from the radio access technologies leading to a new combination of virtualized network core and fronthaul architecture. In this paper, we first investigate the power consumption impact due to the aggressive deployments of low-power neighborhood femtocell networks (NFNs) under the umbrella of a coordinated multipoint (CoMP) macrocell. We show that power savings obtained from employing low power NFN start to decline as the density of deployed femtocells exceed certain threshold. The analysis considers two CoMP sites at the cell-edge and intra-cell areas. Second, to restore the power efficiency and network stabilization, a C-RAN model is proposed to restructure the NFN into clusters to ease the energy burden in the evolving 5G systems. Tailoring this to traffic load, selected clusters will be switched off to save power when they operate with low traffic loads.

Next Generation Optical Access Network Using CWDM Technology

We are developing a novel technology for the next generation optical access network. The proposed architecture provides FTTX high bandwidth which enables to give out 10Gbit/s per end-user. Increasing the subscribers in the future will cause massive congestion in the data transferred along the optical network. Our solution is using the wavelength division multiplexing PON (CWDM-PON) technology to achieve high bandwidth and enormous data transmission at the network access. Physical layer modifications are used in our model to provide satisfactory solution for the bandwidth needs. Thus high data rates can be achieved throughout the network using low cost technologies. Framework estimations are evaluated to prove the intended model success and reliability. Our argument that: this modification will submit a wide bandwidth suitable for the future Internet.

Energy Efficiency using Cloud Management of LTE Networks Employing Fronthaul and Virtualized Baseband Processing Pool

The cloud radio access network (C-RAN) emerges as one of the future solutions to handle the ever-growing data traffic, which is beyond the physical resources of current mobile networks. The C-RAN decouples the traffic management operations from the radio access technologies, leading to a new combination of a virtualized network core and a fronthaul architecture. This new resource coordination provides the necessary network control to manage dense Long-Term Evolution (LTE) networks overlaid with femtocells. However, the energy expenditure poses a major challenge for a typical C-RAN that consists of extended virtualized processing units and dense fronthaul data interfaces. In response to the power efficiency requirements and dynamic changes in traffic, this paper proposes C-RAN solutions and algorithms that compute the optimal backup topology and network mapping solution while denying interfacing requests from low-flow or inactive femtocells. A graph-coloring scheme is developed to label new formulated fronthaul clusters of femtocells using power as the performance metric. Additional power savings are obtained through efficient allocations of the virtualized baseband units (BBUs) subject to the arrival rate of active fronthaul interfacing requests. Moreover, the proposed solutions are used to reduce power consumption for virtualized LTE networks operating in the Wi-Fi spectrum band. The virtualized network core use the traffic load variations to determine those femtocells who are unable to transmit to switch them off for additional power savings. The simulation results demonstrate an efficient performance of the given solutions in large-scale network models.

Spectrum Handoff Management in Cognitive HetNet Systems Overlaid With Femtocells

Cognitive radio networks can facilitate seamless mobility to users considering their effective use of the dynamic spectrum access. This is performed by proactive/reactive adaptation of transmission operations in response to the wireless environment changes. One of these operations includes handoff between various wireless domains. The handoff here is not just a registration with a new base station, but it is also a negotiation to get access to the available channels locally in coexistence with the primary users. This dynamic adaptation between channels, known as spectrum handoff (SH), significantly impacts the time of handoff reconnection, which raises many questions about the functioning of the cognitive radio solution in the next generation of network systems. Therefore, it is necessary to develop a new method for roaming mobile users, particularly networks that employ small cells such as femtocells in order to reduce the unnecessary channel adaptations. This paper proposes a new entity, namely, channel assigning agent for managing SH, operator database, and channel access authentication. The goal of this mechanism is to retain the same channel used by a mobile user whenever possible to improve network performance by reducing the unnecessary SHs. The modeling and efficiency of the proposed scheme are validated through simulation results. The proposed solution improves the accessibility of resources and stability of mobile radio connections that benefits mobile users as well as operators.

Adaptive Management of Cognitive Radio Networks Employing Femtocells

Network planning and management are challenging issues in a two-tier network. Tailoring to cognitive radio networks (CRNs), network operations and transmissions become more challenging due to the dynamic spectrum availability. This paper proposes an adaptive network management system that provides switching between different CRN management structures in response to the spectrum availability and changes in the service time required for the radio access. The considered network management system includes conventional macrocell-only structure, and centralized/distributed structures overlaid with femtocells. Furthermore, analytical expressions of per-tier successful connection probability and throughput are provided to characterize the network performance for different network managements. Spectrum access in dynamic radio environments is formulated according to the quality of service (QoS) constraint that is related to the connection probability and outage probability. Results show that the proposed intelligent network management system improves the maximum capacity and reduces the number of blocked connections by adapting between various network managements in response to free spectrum transmission slots. A road map for the deployment and management of cognitive macro/femto networks is also presented.

Spectrum allocation techniques for industrial smart grid infrastructure

5G research shows more potential attention to mobile communications in information intensive industrial sectors such as power utility. In smart grid context, employing licensed assisted access (LAA) allows smart grid operators to transfer utility data between different sites using the unlicensed and licensed bands. This can play a crucial role in improving efficiency, sustainability, stability, and to meet the quality of service (QoS) requirements of different smart grid consumer requests. Considering the unlicensed band, there is a strong need to develop new LAA unlicensed access technology that can improve spectrum acceptability compared to conventional Wi-Fi to meet the high volumes of information in smart grids. In this paper, we investigate the spectrum allocation techniques required to exploit smart grid requirements by setting a minimum bit error rate (BER) threshold while evaluating the availability of white holes in the unlicensed band. Simulation results confirm the advantages of the proposed scheme in allocating more resources to LAA unlicensed users subject to their load requirements. This paper provides a new method for intelligent spectrum allocation to support the communication requirements of smart grid networks.