Increase Network Capacity Research Articles

Feasibility Study of Power Line Communications for Backhauling Outdoor Small Cells

Small cells are low-power and low-range radio access nodes that can be used to increase network capacity in reduced areas with high traffic demand and to provide coverage to small isolated zones. As their number is expected to be very high, connecting them to the aggregation point in a cost-efficient manner is a key challenge, and there is consensus that none of the current technologies is valid for all scenarios. Since lamp-posts are one of the most convenient locations for outdoor small cells, this work analyzes the use of power line communications (PLC) over outdoor public lighting networks (OPLN) as a backhaul technology for outdoor small cell deployments. To this end, the characteristics of the PLC channels established in OPLN are firstly assessed. The analysis combines noise measurements performed in existing OPLN and channel responses obtained from a multiconductor transmission line (MTL) model. The attenuation, delay spread and spatial correlation of the multiple-input multiple-output (MIMO) channels are investigated and their influence in the physical layer parameters of PLC systems is discussed. Afterward, the performance achieved by state-of-the-art PLC systems is assessed. To this end, estimations obtained by means of simulations and measurements taken in actual networks are included. Data throughput achieved by PLC systems based on the ITU-T G.hn standard, as well as the expected improvements obtained by $3\times 3$ MIMO systems, are given. Results indicate that PLC can be an interesting technology for coverage-driven small cell deployments with backhaul length shorter than 150 m, offering throughput values similar to existing Sub-6 GHz wireless solutions in non-line-of-sight (NLOS) conditions and wired ones like G.fast.

Interference Mitigation for Dynamic TDD Networks Employing Sounding Signals

The requirements of fifth-generation (5G) mobile communications include services with low delay and high throughput. Network densification is pointed to as a promising method to increase the network capacity. However, this solution brings new problems, such as the fast variation in traffic demands among access nodes (ANs) and between uplink and downlink, leading to high delays. To solve the traffic issues in dense networks, dynamic time division duplex (DTDD) is pointed as a possible solution. This strategy creates a new kind of interference between ANs and user equipments (UEs) called cross-interference. Therefore, obtaining channel state information (CSI) of cross-interference channels is essential for implementing interference mitigation methods, such as interference alignment, coordinated beamforming, resource schedulers, among others. Hence, this work proposes methods to estimate the intended and interfering channels based on sounding reference signal (SRS) and/or demodulation reference signal (DMRS). A coordinated scheme is developed to assign sounding signals in the network and reduce the interference perceived during the channel sounding, which improves the channel estimation quality. Furthermore, a refined successive interference cancellation (SIC) algorithm is proposed for estimating the channel. To assess system performance, a zero-forcing beamforming algorithm has been developed based on the CSI acquired with the proposed methods. This algorithm handles the degrees of freedom issues when ANs are operating in opposite directions. The numerical results show that the improved channel quality provided by the proposed estimation algorithm increases network capacity.

Energy-Efficient vBBU Migration and Wavelength Reassignment in Cloud-Fog RAN

Cloud-Fog Radio Access Network (CF-RAN) is a new architecture that increases network capacity in Cloud RAN (CRAN) by moving some BaseBand Units (BBU) from cloud to fog nodes closer to Remote Radio Heads (RRH). However, fog nodes increases CapEx and OpEx. Moreover, tidal traffic fluctuations may lead to an energy-inefficient operation if resources becomes lightly loaded. To address this problem, BBUs of fog nodes could be dynamically activated, and following traffic fluctuations, migrated to cloud. By leveraging Network Functions Virtualization (NFV), virtualized BBUs (vBBUs) can be dynamically allocated, deallocated, and migrated from fog nodes to cloud. Moreover, considering a Time-and-Wavelength Division Multiplexed Passive Optical Network (TWDM-PON) fronthaul, traffic can be migrated among virtual Passive Optical Network (VPON) channels to optimize bandwidth usage. In this article, we propose an Integer Linear Programing (ILP) formulation and an algorithm based on its linear relaxation to solve this migration problem. Compared to an algorithm without migration capabilities, our proposals reduces blocking of RRHs demanding processing of 89% and achieves power savings of 38% by reducing activated processing resources and VPONs after migrations, while experiencing small rates of service interruption. Our relaxation-based solution approximates ILP optimality and reduces execution time of ILP up to 50 ×.

Optoelectronic Hybrid Network Architecture and Its Performance Analysis

Optoelectrical hybrid network technology is introduced into a network based on pure electrical packet switching, which increases network capacity and reduces power consumption. However, the problems of long configuration time and complex management of optical circuit switches affect the performance of hybrid optoelectrical networks. A new type of hybrid optoelectronic network architecture (HOEP) cooperated by Ethernet packet switching network and optical wavelength routing network was designed in the study. The optical routing network transmitted and received optical signals by using a circular array waveguide grating router, and transmitted the optical signal carrying data to the target port based on the characteristics of wavelength cyclic routing. The entire process only needed to modulate the data signal, and did not need to configure the optical wavelength routing network. At the same time, in order to further improve the resource utilization of optical nodes, a kind of intelligent node dynamic reconstruction (RC) algorithm was designed. Combining with network link utilization, cache occupancy, and network load value, this method could dynamically adjust the usage distribution of optical nodes for reconstruction. During the experiment, the RC algorithm was applied to the HOEP network architecture. Compared with other typical network architectures, the HOEP network proposed in the study can effectively reduce the network cost, power consumption, and improve network throughput. Moreover, the introduction of RC algorithm and network equipment can make the cost remain within the controllable range, while it can further increase the network throughput and reduce the power consumption of the HOEP network, thereby meeting the dynamic demand for network bandwidth with larger data traffic.

Channel assignment mechanism for cognitive radio network with rate adaptation and guard band awareness: batching perspective

Cognitive radio (CR) is a promising technology that allows devices to effectively utilize the underutilized or unutilized portions of the licensed spectrum. In literature, several channel assignment and spectrum sharing algorithms for CR Networks (CRNs) have been developed to improve spectrum efficiency without considering the problem of Adjacent Channel Interference (ACI). Guard-Band (GB)-aware mechanisms have been proposed in CRNs to prevent ACI and improve spectrum efficiency. However, most of the existing GB-aware algorithms assume having channels with fixed-rate and employ a sequential channel assignment paradigm. Unfortunately, this assumption is not realistic, because channel’s conditions may vary over time. In this work, we propose a GB-aware channel assignment that considers the channel-dependent achieved transmission rates (due to Rayleigh fading time-varying conditions) at different time slots while simultaneously assigning channels to several CR transmissions. This batch based proposal aims at increasing network capacity and minimizing the number of assigned channels per user subject to rate demand and interference constraints. Simulation experiments demonstrate the effectiveness of our proposed scheme, which show a significant improvement in network performance in terms of the number of served CR users.

Doherty PAs for 5G Massive MIMO: Energy-Efficient Integrated DPA MMICs for Sub-6-GHz and mm-Wave 5G Massive MIMO Systems

To accommodate growing user demand for faster data rates and extensive connectivity, modern wireless communication systems must evolve to support a sharply increasing number of subscribers, all requesting service at the same time. This trend encourages the broad application of multiple input/multiple output (MIMO) systems. In fact, MIMO techniques can increase data rates, coverage of service areas, and communication reliability without additional RFs. In recent proposals for 5G systems, the required separate RF chains in massive MIMO RF front ends can reach up to 256, with bandwidths of up to 800 MHz per RF chain [1], [2]. Massive MIMO is a critical technology that helps significantly in increasing network capacity and spectral efficiency, while reducing wireless network interference, ultimately improving the end-user experience.

Securing Channel State Information in Multiuser MIMO With Limited Feedback

The potential of multiuser MIMO (MU-MIMO) to increase network capacity has been intensively studied. To enable concurrent transmission in Frequency-Division Duplex (FDD) systems with limited feedback, users have to report the estimated channel state information (CSI) to the base station (BS) for interference elimination, which however has been proven to be vulnerable. In this paper, we reveal how to utilize the CSI feedbacks to launch sniffing attacks in a deterministic way, where the sniffing attack enables the attackers to eavesdrop other users in the same transmission group. We conduct a rigorous theoretical analysis on the construction of the forged CSI. In the proposed sniffing attacks, the malicious users can successfully sniff other users’ messages without knowing their own messages for signal cancellation. To make sniffing attacks more practical, we explore the possibilities of sniffing multiple users by a coalition of malicious users or a single malicious user. To thwart sniffing attacks, we design a novel secure CSI feedback (SCF) protocol based on the random masking technique, which requires simple modifications at the BS and incurs a little additional workload. Extensive theoretical analysis and experimental results are provided to further validate the effectiveness of our proposed sniffing attacks and the corresponding countermeasure.

Scheduling Wireless Links in the Physical Interference Model by Fractional Edge Coloring

We consider the problem of scheduling the links of wireless mesh networks for capacity maximization in the physical interference model. We represent such a network by an undirected graph $G$, with vertices standing for network nodes and edges for links. We define network capacity to be $1/\chi'^*_\mathrm{phys}(G)$, where $\chi'^*_\mathrm{phys}(G)$ is a novel edge-chromatic indicator of $G$, one that modifies the notion of $G$'s fractional chromatic index. This index asks that the edges of $G$ be covered by matchings in a certain optimal way. The new indicator does the same, but requires additionally that the matchings used be all feasible in the sense of the physical interference model. Sometimes the resulting optimal covering of $G$'s edge set by feasible matchings is simply a partition of the edge set. In such cases, the index $\chi'^*_\mathrm{phys}(G)$ becomes the particular case that we denote by $\chi'_\mathrm{phys}(G)$, a similar modification of $G$'s well-known chromatic index. We formulate the exact computation of $\chi'^*_\mathrm{phys}(G)$ as a linear programming problem, which we solve for an extensive collection of random geometric graphs used to instantiate networks in the physical interference model. We have found that, depending on node density (number of nodes per unit deployment area), often $G$ is such that $\chi'^*_\mathrm{phys}(G)<\chi'_\mathrm{phys}(G)$. This bespeaks the possibility of increased network capacity by virtue of simply defining it so that edges are colored in the fractional, rather than the integer, sense.

Minimizing Interference in Ultra-Dense Femtocell Networks Using Graph-Based Frequency Reuse Technique

This paper investigates the performance of graph colouring schemes for frequency assignment in Long-Term Evolution (LTE) networks with ultra-dense femtocells. The aim of the study is to minimize interference in such networks while ensuring efficient spectrum use for these femtocells. The three schemes investigated are the conventional greedy graph colouring algorithm, the saturation degree algorithm and our proposed graph-based theory (GBT) algorithm. The process of frequency assignment is similar in the last two except that the proposed GBT partitions the femtocells into independent sets for an efficient frequency re-use. The performance of these three schemes was analyzed through extensive simulations to determine the SINR and network capacity that can be obtained with the deployment of these schemes using the ITU-R P1238-7 path loss model. The outcome of this study showed that with the absence of a dynamic frequency assignment scheme, interference level is increased as the number of femtocell users within a particular coverage is increased, leading to a reduction in the capacity of such networks. Simulation results showed that all three algorithms considered have the ability to allocate frequencies to femtocells and minimize interference in a densely deployed environment, thereby increasing network capacity. The proposed GBT assigned the least sub-band thereby ensuring spectral efficiency while minimizing harmful interference. Results show that the greedy algorithm has a disadvantage of inefficiently assigning sub-bands randomly, while the saturation degree assigns more sub-bands when compared with the GBT scheme.Keywords — Femtocell, graph colouring, frequency assignment, LTE.

Two-phase optimization model for ride-sharing with transfers in short-notice evacuations

Optimization of on-demand transportation provisions and ride-sharing services in evacuations may provide increased network capacity and enhanced evacuation performance to transportation systems and improve equity and disaster preparedness for community and society. This paper proposes a two-phase model for optimizing trip planning and operations by integrating a ride-sharing process in short-notice evacuations, to allow a joint optimization of driver-rider matching and necessary transfer connections among shared vehicle trips. In the first phase, following network topology information and personal requests, a vehicle-space-time hyper dimensional network is developed by constructing vehicle-space-time vertexes and arcs. In the second phase, based on the constructed vehicle-space-time network, a new time-discretized multi-rider multi-driver network flow model is built to formulate ride-sharing with connecting transfers. A Lagrangian relaxation solution approach is designed to solve the model in a real-world network scenario. Numerical analyses are conducted with considerations given to the three operating parameters (detour tolerance of driver, penalty factor for transfer time, and maximum allowable parking time) in the method, and the analysis results show that the proposed model can not only meet the evacuation trip needs of the participating parties but it also supports personalized requests and on-demand accesses. A small sample network is used to theoretically test the whole model and the underlying concepts and solution strategy to show each step implemented in details, and finally the applicability of the method is demonstrated using the Chicago City network.

Self-Adaptive Neighbor Discovery in Wireless Sensor Networks with Sectored-Antennas

Integration of sectored antenna in wireless networks improves network performance through increased network capacity and extended transmission range. However, incorporating sectored antenna makes the trivial process of discovering neighbors even more challenging and complicated. Moreover, due to the duty-cycled nature of Wireless Sensor Networks (WSNs), self-adaptive and distributed neighbor discovery mechanisms are highly sought-after. In this paper, we present a Neighbor Discovery with Sectored Antenna (NDSA) protocol for WSNs with the sectored antenna. NDSA distinguish itself from other protocols in four distinct ways. Firstly, the introduction of super-frame like structure to support the duty-cycled operation of WSNs. Secondly, the protocol adapts its operation according to the network dynamics by leveraging the in-network information. Thirdly, a cooperative mechanism through which nodes utilize the information about their discovered neighbors to avoid an excessive exchange of control messages. Finally, handling the channel access details to discover neighbors faster with fewer message collisions. Through a comprehensive simulation-based study, the results show that the proposed protocol outperformed the random and serialized approaches to neighbor discovery in terms of discovery latency while significantly minimizing the communication overhead.

Resource Allocation and Power Control Policy for Device-to-Device Communication Using Multi-Agent Reinforcement Learning

Device-to-Device (D2D) communication is a promising technology that can reduce the burden on cellular networks while increasing network capacity. In this paper, we focus on the channel resource allocation and power control to improve the system resource utilization and network throughput. Firstly, we treat each D2D pair as an independent agent. Each agent makes decisions based on the local channel states information observed by itself. The multi-agent Reinforcement Learning (RL) algorithm is proposed for our multi-user system. We assume that the D2D pair do not possess any information on the availability and quality of the resource block to be selected, so the problem is modeled as a stochastic non-cooperative game. Hence, each agent becomes a player and they make decisions together to achieve global optimization. Thereby, the multi-agent Q-learning algorithm based on game theory is established. Secondly, in order to accelerate the convergence rate of multi-agent Q-learning, we consider a power allocation strategy based on Fuzzy Cmeans (FCM) algorithm. The strategy firstly groups the D2D users by FCM, and treats each group as an agent, and then performs multi-agent Q-learning algorithm to determine the power for each group of D2D users. The simulation results show that the Q-learning algorithm based on multi-agent can improve the throughput of the system. In particular, FCM can greatly speed up the convergence of the multi-agent Q-learning algorithm while improving system throughput.

A channel assignment scheme for MIMO on concentric-hexagon-based multi-channel wireless networks

In a wireless network, multiple channels can increase network capacity. However, it causes other problems, e.g., multi-channel hidden terminal problem and the issue about how to allocate channels to wireless nodes. Basically, a well-defined channel assignment can avoid radio interference and improve transmission performance. Therefore, in this study, we proposed a multiple channel assignment scheme, called concentric-hexagon-oriented multi-channel assignment (CHOMA for short), in which all deployed eNBs are organized as concentric-hexagon (C-hexa for short). Available channels are grouped and then allocated to the C-hexas. We also arrange channels allocated to a C-hexa so as to reduce radio interference among its eNBs, consequentially improving the transmission capability and performance of a wireless network. Experimental results show that the CHOMA is really an interference-free scheme, no matter whether the target system is a network with SISO, SIMO, MISO or MIMO stations.

A channel assignment scheme for MIMO on concentric-hexagon-based multi-channel wireless networks

In a wireless network, multiple channels can increase network capacity. However, it causes other problems, e.g., multi-channel hidden terminal problem and the issue about how to allocate channels to wireless nodes. Basically, a well-defined channel assignment can avoid radio interference and improve transmission performance. Therefore, in this study, we proposed a multiple channel assignment scheme, called concentric-hexagon-oriented multi-channel assignment (CHOMA for short), in which all deployed eNBs are organized as concentric-hexagon (C-hexa for short). Available channels are grouped and then allocated to the C-hexas. We also arrange channels allocated to a C-hexa so as to reduce radio interference among its eNBs, consequentially improving the transmission capability and performance of a wireless network. Experimental results show that the CHOMA is really an interference-free scheme, no matter whether the target system is a network with SISO, SIMO, MISO or MIMO stations.

Gradual Migration of Co-Existing Fixed/Flexible Optical Networks for Cloud-Fog Computing

Fog computing emerges as a great candidate to mitigate the unsolved problems of cloud computing. Data migration between fog nodes and datacenters is placing huge bandwidth requirements on substrate optical networks. To increase network capacity and to improve network flexibility, broad attention has been given to flexible-grid technology. This paper addresses the issue of how to migrate substrate optical networks from the fixed-grid network era to the flexible-grid network era gradually, due to the unbearable capital expenditure and service stability. First, we model the network migration and elucidate the upgrade probability by calculating the node demands for upgrading. Then, based on the upgrade probability, three schemes are proposed to construct Potential Upgrade Nodes Group (PUNG). Besides, to maintain the traffic stability, a Migration-aware Service Provisioning (MSP) scheme is proposed based on PUNG. Numerical results illustrate that the proposed MSP scheme can effectively enhance the traffic stability compared to Non-migration-aware Service Provisioning (NSP) scheme, and the connection interrupted ratio is excessively reduced.

AN INVESTIGATION AND IMPLEMENTATION OF WIDEBAND DIELECTRIC RESONATOR ANTENNA FOR 5G WIRELESS COMMUNICATIONS

The comprehensive deployments of 5G networks are at a fast pace and are predictable to deliver extraordinary data rate, little latency rate, effective Electro Magnetic spectrum exploitation compared to 4G. To increase network capacity, the 5G NR air interface allows a diverse spectrum in the sub-6 GHz frequency bands. The Proposal includes current technologies on Fifth Generation multiband square dielectric resonator antenna for the future wireless communication system. A diverse Dielectric Resonator Antenna (DRA) is accessible on behalf of wide-ranging band applications; wideband DRA design improves three aspects: a compact T-shaped rectangular dielectric resonator, a correct angle between directions within small areas for reversed trapezoid micro strip as a feed mechanism, and an RT Duroid 5880 substrate as a base. Furthermore, a conventional square DRA of the same frequency for the determination of comparison is designed. The projected dielectric antenna resonating from 3 to 5.7 GHz with 2.78 GHz of extensive impedance bandwidth in which it covers the targeted 5G bands up to sub-6 GHz, having a good return loss below -10 dB. Additionally, the suggested DRA has an extreme radiation efficiency of 98.3%>97.7% complete radiation efficiency and maximum gain is 5.93 dBi. Alternatively, the proposed DRA will resonate at 3.8 GHz with 302 MHz of restrained impedance bandwidth, having reasonable return loss. The proposed antennas are simulated using the 3D EM simulation tool of CST Microwave studio. Together they suggested antennas consume a closely omnidirectional radiation pattern at resonance frequencies, through VSWR<2. Relative study of the double suggested antennas regarding return loss, impedance bandwidth, VSWR, radiation pattern, and gain obviously. It illustrates the performance of T-shaped DRA over rectangular DRA at 5G is a good agreement.

A Comprehensive Survey on Mobility Management in 5G Heterogeneous Networks: Architectures, Challenges and Solutions

With the rapid increase in the number of mobile users, wireless access technologies are evolving to provide mobile users with high data rates and support new applications that include both human and machine-type communications. Heterogeneous networks (HetNets), created by the joint installation of macro cells and a large number of densely deployed small cells, are considered an important solution to deal with the increasing network capacity demands and provide high coverage to wireless users in future fifth generation (5G) wireless networks. Due to the increasing complexity of network topology in 5G HetNets with the integration of many different base station types, in 5G architecture mobility management has many challenges. Intense deployment of small cells, along with many advantages it provides, brings important mobility management problems such as frequent handover (HO), HO failure, HO delays, ping-pong HO and high energy consumption which will result in lower user experience and heavy signal loads. In this paper, we provide a comprehensive study on the mobility management in 5G HetNet in terms of radio resource control, the initial access and registration procedure of the user equipment (UE) to the network, the paging procedure that provides the location of the UE within the network, connected mode mobility management schemes, beam level mobility and beam management. Besides, this paper addresses the challenges and suggest possible solutions for the 5G mobility management.

Multi-RAT Aggregation Through Spectrum Reallocation for Future Wireless Networks

Next generation wireless networks are becoming the main focus of the industry by putting efforts to launch beyond 4G (i.e. 5G) communication systems by 2020. Towards the 5G-system vision, the efficient spectrum aggregation by integrating multiple radio access technologies (multi-RAT) is one of the enablers to achieve the highest data rates. To this end, a multi-RAT aggregation is envisioned that can be provided using the spectrum reallocation technique. Spectrum reallocation among multi-RATs can provide spectrum opportunities for aggregation and, thus, the overall spectrum utilization and network capacity increase. Maintaining an optimum quality of experience (QoE) for users of different RATs in such an extremely complex network environment can be facilitated by such a multi-RAT aggregation (spectrum aggregation from different RATs), through spectrum reallocation. To this end, both network and functional architectures are specified and spectrum assignment solutions are proposed in this article. The goal is to efficiently increase the data rates supporting a required QoE for all users.

AdaptFlow: Adaptive Flow Forwarding Scheme for Software-Defined Industrial Networks

Industry 4.0 revolution has emerged as an escalator for increased productivity and cost savings in smart factories. However, they pose a big challenge for network architecture in providing a flexible way for continuous data flow. The necessity of reliable connectivity in the industrial ecosystem has paved the path for the evolution of software-defined industrial networks. However, the nature of data traffic in the industrial environment further pushes the need for adaptive flow forwarding and control. Therefore, in this article, AdaptFlow, an adaptive flow forwarding scheme, is designed for software-defined industrial networks. AdaptFlow includes: 1) application-specific traffic classification using self-organized maps; 2) B+ tree-based flow table management; 3) queuing model for analyzing the waiting time; and 4) energy-aware flow forwarding algorithm. The evaluation of AdaptFlow scheme shows improvements in minimizing delay and energy consumption while increasing network capacity in contrast to the OpenFlow architecture.

Resource Management in LTE-U Systems: Past, Present, and Future

With the tremendous growth in mobile data traffic, wireless cellular networks are facing a rigorous challenge to increase network capacity. Despite that many advanced technologies are used, the shortage of spectrum resource is still the main bottleneck for capacity enhancement. To address the challenge, the cellular networks have been motivated to seek for more fruitful radio spectra. Amongst many others, the unlicensed 5 GHz spectrum is a promising candidate due to its low channel attenuation, large available bandwidth, and easy to utilize. Therefore, the innovative technology of long-term evolution (LTE) using the unlicensed spectrum, known as LTE-Unlicensed (LTE-U), has been widely investigated as a promising means to increase the data rate of cellular networks. The unique characteristics of the unlicensed spectrum bring new challenges to resource management in the LTE-U system. During the last few years, there have been a lot of resource management designs for the newly-born but vigorous LTE-U technologies. This paper provides a comprehensive overview of the state-of-the-art resource management scenarios in LTE-U systems, including single small cell base station (SBS), multiple SBSs, device-to-device (D2D) networks, vehicular networks, and unmanned aerial vehicle (UAV) systems. The future research issues of resource management in LTE-U for 5G are also outlined.