Energy-Efficient Access Scheme with Joint Consideration on Backhauling in UDN

The ultra-dense network (UDN) is one of the most promising technologies in the fifth generation (5G) to address the network system capacity issue. However, it is a new challenge that the user equipment (UE) secure access UDN composed of the access points (APs) which characterized with autonomy, temporary, and dynamic. In 5G UDN, the APs are independent and equal. The UDN can be regarded as a decentralized access network. Compared with the traditional base station, the AP has a smaller coverage. There has an issue that the interaction between the UE and APs will be more frequent when UE moves. However, the existing 4G authentication and key agreement algorithm cannot adapt to this fast and frequent authentication requirement. If the UE moves smoothly in a trusted APs group (APG) without frequent authentication, this problem will be solved very well. In order to achieve this goal, we propose a security authentication scheme of 5G UDN based on the block chaining technologies. In this paper, an APG-PBFT algorithm based on the block chaining technology with Byzantine fault tolerance (PBFT) consensus algorithm is proposed. In the algorithm, the consensus mechanism will be optimized and a new reverse screening method will be embedded. In our solution, a trusted chain APG can be generated with APs by APG-PBFT algorithm, and the authentication results can be shared in the APG using the blockchain message propagation mechanism. The principle of fast authentication with APG-PBFT algorithm is present in this paper. The scheme can reduce the authentication frequency when UE moves among the APs and improve the access efficiency. Finally, we analyze the performance of APG-PBFT algorithm and compare it with the traditional PBFT algorithm. The simulation results show that the APG-PBFT algorithm can improve the APG generation efficiency and reduce the authentication frequency of UE, which will be valuably applied to the UDN environment.

SummarySmall cell networks can fulfill the increasing demandfor the high data rate of wireless applications. Energy efficiency is an important design parameter of the ultra dense small cell network (UDSCN). The sleeping strategy of small base stations (s‐BSs) is used to enhance the network's energy efficiency. An efficient sleeping strategy of s‐BSs is required while preserving users' quality of service (QoS). The idle s‐BSs can be switched to sleep mode. This paper proposes a blockchain‐enabled solution for the sleeping strategy of s‐BSs. Here, a blockchain‐enabled small cell network is created between the s‐BSs. The network is decentralized, which eliminates the workload of the macro base station (MBS). The proposed network architecture is enabled as a decentralized network through blockchain. The blockchain provides distributed control over the s‐BS operations through a smart contract. Here, smart contracts act as distributed self organizing network features to handle self‐transactions among small cells for switching off s‐BSs in the network. All the software logic required to perform s‐BS operations is written in a smart contract using Ethereum. The proposed solution improves energy efficiency and enables the ultra dense small cell network to be decentralized.

The amorphous multi-connected networks have e-merged as a new trend to meet the fast increasing wireless capacity and coverage demands of future 5G networks. To realize such amorphous networks, ultra dense network (UDN) technology is expected as a promising candidate for its flexible network architecture and abundant radio resources. Yet, the multi-connection optimization for UDN is still left as an open problem nowadays. This motivates us to explore how many and which access points (APs) should be accessed in multi-connected amorphous UDNs. To solve this problem, we introduce a new definition of the maximum number of accessed APs for help, and propose two algorithms to identify this number and handle the AP selection respectively. Monte Carlo simulations testify the validity of our scheme and prove that our strategy can guarantee the soft handover and overcome the “ping-pong effect” efficiently in various kinds of networks with high sum-rate performance.

The heterogeneous ultra-dense network (UDN) has been widely regarded as a promising architecture for coping with the massive data traffic in future mobile networks including fifth generation mobile networks. There have been innumerable research efforts toward boosting the capacity of UDNs. Global communication path orchestration can better utilize UDN capacity; unfortunately, few studies focus on this topic. In this article, we propose a communication path orchestration architecture for heterogeneous UDNs. In this architecture, data can be transported from one interior communication node (i.e., a base station or user device) to another interior node along a hybrid device communication path (HDCP). HDCPs can be used for communications between two user devices and can be used to migrate traffic between backhaul links. Application- layer-assisted data forwarding allows HDCP to include various communication links including access links, backhaul links, and device-to-device links using licensed and unlicensed spectrum resources. HDCPs are centrally arranged to meet specific requirements and designated optimization objectives. We introduce two HDCP orchestration methods in this article. Our proposed solution can be used as a significant supplement to existing techniques for heterogeneous UDNs.

Due to the new characteristics of ultra-dense networks (UDN), such as high dense deployment of wireless access points (APs), complicated handover signaling processes and irregular coverage, how to achieve mobility support and reduce user's interrupt ratio remain a difficult problem. To address these issues, based on the presented user-centric APs clustering (UCC) network architecture in UDN, a UCC method is proposed. In the scheme, with dynamic refreshment of the UCC member, a user equipment (UE) moves as if it is surrounded by the connected APs and the AP-to-AP handover is concealed. In order to provide UE with satisfactory services, the UCC is formulated based on the joint transmission benefit. Additionally, UCC member refreshing algorithm is designed to facilitate seamless connectivity with new APs. Finally, performance analysis is done. Compared to the anchor-based scheme, we simulate our scheme from three aspects, including interrupt ratio, spectral efficiency and user average rate.

A survey on user-centric cell-free massive MIMO systems

Solving the main optimization problem, including a large number of access points and user equipment in ultra-dense networks (UDNs) using the Munkres algorithm, is a time-consuming solution. In this paper, we propose two new ideas for selecting the appropriate access points (APs) in UDNs that reduce the complexity order and find the suboptimum solution efficiently. Applying the first idea, all user equipment (UE) that are out of access points' service area and all access points that cannot find any user equipment in their service area are removed. In this case, the solutions of the conventional and proposed version of the Munkres algorithm are the same, which offers a high total sum value of the signal to noise ratios (SNRs). Still, it does not guarantee minimum interference. Hence, as the second idea, we consider estimation of the signal to interference plus noise ratio (SINR), entitled by average-SINR and random-SINR, and solve the optimization problem, including a large number of access points and a variable number of user equipment densely distributed. The simulation results show the effectiveness of the proposed algorithms in the view of sum-rate, the number of successful user equipment, and computational complexity for an area, including 250 APs and a variable number of UEs.

The massive growth of data consumption and the variety of wireless technology emergence has made the handover (HO) an attractive research topic nowadays, mainly due to the popularity of Wireless Local Area Networks (WLANs), which allow users to reach high-speed data communication while they are in movement. Moreover, mobile devices such as tablets and smartphones have also become increasingly popular due to their low cost and ease of use, and an increase in mobile device use is expected to accelerate in the coming years, along with the availability and use of applications such as real-time services and online gaming. The traditional HO methods will likely not meet the requirements of mobile devices for modern applications due to the lack of intelligence, lack of awareness Quality of Service (QoS) and Quality of Experience (QoE) requirements of mobile users. We, therefore, introduce a novel architecture that supports horizontal HO in homogenous networks. This architecture is based on the Software-Defined Wireless Networking (SDWN) concept, where the wireless network is controlled centrally and the wireless Access Points (APs) are programmable. In this architecture, HO algorithms will assist wireless users to find the network that could best support the application requirements through Quality of Service (QoS) and Quality of Experience (QoE) management policies. The first HO algorithm proposed in this thesis is called Quality of Experience Oriented Handover Algorithm. This algorithm will guarantee the best possible connectivity to the users in terms of their QoE and QoS requirements and outperforms the traditional methods in a sparse network environment. The second contribution is called Optimised Handover Algorithm for Dense WLAN Environments. This algorithm has been designed to address dense network environments via taking into consideration the Adaptive Hysteresis Value (AHV). The AHV will help the Optimised Handover Algorithm via reducing the so-called ping-pong effect. This contribution shows promising performance results by selecting the best candidate AP, decreasing the number of redundant HO and avoiding the ping-pong effect. The final contribution is called Priority Based Handover Algorithm. We extended our proposed SDWN architecture in order to include the concept of prioritising users and make a smart decision during the process of HO. This algorithm will prioritise a certain class of users to avoid the effect of the over-congestion. The results show that the approach based on priority outperforms the state of the art and provides better QoE to the high priority users despite the over-congestion situation.

In ultra dense WiFi networks, access points are deployed with high density in order to support Internet access for large amount of mobile users at the same time. Since the mobile users may not be uniformly distributed in the network, the heavy loaded access points and the interference among different access points would cause the network throughput degradation. Further, although increasing transmission power levels of access points could enhance network throughput, the energy efficiency would be low. Energy consumption is an increasingly important issue today so that the network performance needs to be improved in an energy efficient manner. Under this condition, we propose a distributed power adjustment scheme to intelligently maximize the throughput of the entire network without increasing transmission power in the presence of dynamic distributed mobile users. To validate the performance of our proposed scheme, we simulate various network conditions and the results show that our proposed scheme can sustain throughput with less energy consumption with less than 200 iterations.

The advancement of integrated millimeter-wave products opens the possibility of leveraging communications in 60-GHz band to meet the unprecedented traffic demand in WLAN. Despite the vast bandwidth available, millimeter-wave signals suffer from high attenuation and weak diffraction ability. Therefore, wireless communication at 60 GHz is characterized by the inherent directivity and susceptibility to blockage. Multiple Access Point (AP) architecture is proposed for 60-GHz WLAN to enhance spatial reuse and survive blockage. In the presence of multiple APs in the network, this paper addresses the important problem of user-AP association and resource allocation. We study three schemes of different complexity and investigate how to maximize user throughput with joint consideration of AP assignment and transmission scheduling. To solve the formulated problem, we propose a branch-and-cut-based solution procedure. We perform a detailed comparative analysis of the three schemes and advocate to use one-shot AP assignment-based scheduling scheme due to its simplicity and good performance. To deal with real-time traffic and human blockage, we propose an online algorithm to implement the one-shot AP assignment-based scheme to avoid frequent service disruption. Our results show that the proposed online algorithm is competitive when compared with the optimal offline algorithm.

In this paper, we propose a general mathematical framework to compute the average downlink rate in a multiple connectivity context considering ultra-dense network (UDN) environment. UDN is a dense small cells network featured by the high density of small cells that may exceed the density of active users. In multiple association, a user connects to M base stations (BSs) that provide the maximum average received power forming a multicell. This provides the user with a “data-shower,” where the user's traffic is split into multiple paths, which helps overcoming the capacity limitations imposed by the backhaul links. The developed framework significantly simplifies the computation of the average downlink rate of the individual connections to the cells of a multicell. Moreover, the accuracy of the mathematical framework is confirmed by extensive simulations. The simulation results show a perfect match with the numerical results computed from the mathematical framework in different combinations of the system parameters including multicell size, small cells density, active users density, pathloss exponent, and fading channel distribution of the signal link.

This paper presents a framework for allocating radio resources to the Access Points (APs) introducing an Access Point Controller (APC). Radio resources can be either time slots or subchannels. The APC assigns subchannels to the APs using a dynamic subchannel allocation scheme. The developed framework evaluates the dynamic subchannel allocation scheme for a downlink multicellular Orthogonal Frequency Division Multiple Access (OFDMA) system. In the considered system, each AP and the associated Mobile Terminals (MTs) are not operating on a frequency channel with fixed bandwidth, rather the channel bandwidth for each AP is dynamically adapted according to the traffic load. The subchannels assignment procedure is based on quality estimations due to the interference measurements and the current traffic load. The traffic load estimation is realized with the measurement of the utilization of the assigned radio resources. The reuse partitioning for the radio resources is done by estimating mutual Signal to Interference Ratio (SIR) of the APs. The developed dynamic subchannel allocation ensures Quality of Service (QoS), better traffic adaptability, and higher spectrum efficiency with less computational complexity.

We consider the cell-free massive multiple-input multiple-output (MIMO) downlink, where a very large number of distributed multiple-antenna access points (APs) serve many single-antenna users in the same time-frequency resource. A simple (distributed) conjugate beamforming scheme is applied at each AP via the use of local channel state information (CSI). This CSI is acquired through time-division duplex operation and the reception of uplink training signals transmitted by the users. We derive a closed-form expression for the spectral efficiency taking into account the effects of channel estimation errors and power control. This closed-form result enables us to analyze the effects of backhaul power consumption, the number of APs, and the number of antennas per AP on the total energy efficiency, as well as, to design an optimal power allocation algorithm. The optimal power allocation algorithm aims at maximizing the total energy efficiency, subject to a per-user spectral efficiency constraint and a per-AP power constraint. Compared with the equal power control, our proposed power allocation scheme can double the total energy efficiency. Furthermore, we propose AP selections schemes, in which each user chooses a subset of APs, to reduce the power consumption caused by the backhaul links. With our proposed AP selection schemes, the total energy efficiency increases significantly, especially for large numbers of APs. Moreover, under a requirement of good quality-of-service for all users, cell-free massive MIMO outperforms the colocated counterpart in terms of energy efficiency.

In order to improve the total system throughput by analyzing the resource allocation problems in backhaul links and access links of base stations in ultra-dense network (UDN), a proportional fair resource allocation (PFRA) algorithm was designed for the wireless hybrid hierarchical backhaul network in this paper. First, the base stations were stratified and the frame structure of each base station in different layeies was re-designed. Then, the objective function was constructed based on the proportional fair utility function to optimize the system throughput. Finally, an iterative algorithm was derived based on Lagrange Multiplier algorithm to obtain the optimal solution of spectrum resource allocation in hybrid hierarchical backhaul network. The performance of the PFRA algorithm has been simulated and the results show that the PFRA algorithm can improve network throughput effectively at the cost of losing a certain network coverage rate. In the future, PFRA needs to be optimized to reach the best balance between network throughput and network coverage rate.

The Ultra Dense Network (UDN), as a key enabler for future wireless networks (such as 5G), is comprised of a massive number of small cells in the network. Nonetheless, energy consumption will be non-negligible when a large number of smallcell Base Stations (BSs) are densely deployed. One practical and effective approach to reduce the energy consumption of the UDN is through dynamically controlling the power saving mode of BSs, while the challenge is to maintain network coverage and satisfy the performance requirements of User Equipment (UEs). In this paper, we formalize the problem of minimizing the energy consumption of BSs by optimally controlling the BS's power saving mode (switching between awake mode and sleep mode). We focus on optimal BS selection with the objective of energy efficiency, while the considering the constraints of the coverage of UEs, the capacity of BSs, and the data rate UEs. To validate the effectiveness of our proposed scheme, we have conducted performance evaluations with a comprehensive scenario design, consisting of UE density, distribution, and mobility, as well as BS deployment. The evaluation results demonstrate favorable energy efficiency improvement at averages of 38.82 % and 48.05 % in scenarios where UEs are uniformly distributed and non-uniformly distributed in the network. Meanwhile, network coverage and UE's Quality of Service (QoS) requirements are provided.