Millimeter-wave Evolution for 5G Cellular Networks

Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.Comment: 17 pages, 12 figures, accepted to be published in IEICE Transactions on Communications. (Mar. 2015

Context Information for Fast Cell Discovery in mm-wave 5G Networks

The exploitation of the mm-wave bands is one of the most promising solutions for 5G mobile radio networks. However, the use of mm-wave technologies in cellular networks is not straightforward due to mm-wave harsh propagation conditions that limit access availability. In order to overcome this obstacle, hybrid network architectures are being considered where mm-wave small cells can exploit an overlay coverage layer based on legacy technology. The additional mm-wave layer can also take advantage of a functional split between control and user plane, that allows to delegate most of the signaling functions to legacy base stations and to gather context information from users for resource optimization. However, mm-wave technology requires high gain antenna systems to compensate for high path loss and limited power, e.g., through the use of multiple antennas for high directivity. Directional transmissions must be also used for the cell discovery and synchronization process, and this can lead to a non-negligible delay due to the need to scan the cell area with multiple transmissions at different directions. In this paper, we propose to exploit the context information related to user position, provided by the separated control plane, to improve the cell discovery procedure and minimize delay. We investigate the fundamental trade-offs of the cell discovery process with directional antennas and the effects of the context information accuracy on its performance. Numerical results are provided to validate our observations.Comment: 6 pages, 8 figures, in Proceedings of European Wireless 201

Obstacle Avoidance Cell Discovery using mm-waves Directive Antennas in 5G Networks

With the advent of next-generation mobile devices, wireless networks must be upgraded to fill the gap between huge user data demands and scarce channel capacity. Mm-waves tech- nologies appear as the key-enabler for the future 5G networks design, exhibiting large bandwidth availability and high data rate. As counterpart, the small wave-length incurs in a harsh signal propagation that limits the transmission range. To overcome this limitation, array of antennas with a relatively high number of small elements are used to exploit beamforming techniques that greatly increase antenna directionality both at base station and user terminal. These very narrow beams are used during data transfer and tracking techniques dynamically adapt the direction according to terminal mobility. During cell discovery when initial synchronization must be acquired, however, directionality can delay the process since the best direction to point the beam is unknown. All space must be scanned using the tradeoff between beam width and transmission range. Some support to speed up the cell search process can come from the new architectures for 5G currently being investigated, where conventional wireless network and mm-waves technologies coexist. In these architecture a functional split between C-plane and U-plane allows to guarantee the continuous availability of a signaling channel through conventional wireless technologies with the opportunity to convey context information from users to network. In this paper, we investigate the use of position information provided by user terminals in order to improve the performance of the cell search process. We analyze mm-wave propagation environment and show how it is possible to take into account of position inaccuracy and reflected rays in presence of obstacle

Novel Resource and Energy Management for 5G Integrated Backhaul/Fronthaul (5G-Crosshaul)

The integration of both fronthaul and backhaul into a single transport network (namely, 5G-Crosshaul) is envisioned for the future 5G transport networks. This requires a fully integrated and unified management of the fronthaul and backhaul resources in a cost-efficient, scalable and flexible way through the deployment of an SDN/NFV control framework. This paper presents the designed 5G-Crosshaul architecture, two selected SDN/NFV applications targeting for cost-efficient resource and energy usage: the Resource Management Application (RMA) and the Energy Management and Monitoring Application (EMMA). The former manages 5G-Crosshaul resources (network, computing and storage resources). The latter is a special version of RMA with the focus on the objectives of optimizing the energy consumption and minimizing the energy footprint of the 5G-Crosshaul infrastructure. Besides, EMMA is applied to the mmWave mesh network and the high speed train scenarios. In particular, we present the key application design with their main components and the interactions with each other and with the control plane, and then we present the proposed application optimization algorithms along with initial results. The first results demonstrate that the proposed RMA is able to cost-efficiently utilize the Crosshaul resources of heterogeneous technologies, while EMMA can achieve significant energy savings through energy-efficient routing of traffic flows. For experiments in real system, we also set up Proof of Concepts (PoCs) for both applications in order to perform real trials in the field.© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Millimeter-wave Wireless LAN and its Extension toward 5G Heterogeneous Networks

Millimeter-wave (mmw) frequency bands, especially 60 GHz unlicensed band, are considered as a promising solution for gigabit short range wireless communication systems. IEEE standard 802.11ad, also known as WiGig, is standardized for the usage of the 60 GHz unlicensed band for wireless local area networks (WLANs). By using this mmw WLAN, multi-Gbps rate can be achieved to support bandwidth-intensive multimedia applications. Exhaustive search along with beamforming (BF) is usually used to overcome 60 GHz channel propagation loss and accomplish data transmissions in such mmw WLANs. Because of its short range transmission with a high susceptibility to path blocking, multiple number of mmw access points (APs) should be used to fully cover a typical target environment for future high capacity multi-Gbps WLANs. Therefore, coordination among mmw APs is highly needed to overcome packet collisions resulting from un-coordinated exhaustive search BF and to increase the total capacity of mmw WLANs. In this paper, we firstly give the current status of mmw WLANs with our developed WiGig AP prototype. Then, we highlight the great need for coordinated transmissions among mmw APs as a key enabler for future high capacity mmw WLANs. Two different types of coordinated mmw WLAN architecture are introduced. One is the distributed antenna type architecture to realize centralized coordination, while the other is an autonomous coordination with the assistance of legacy Wi-Fi signaling. Moreover, two heterogeneous network (HetNet) architectures are also introduced to efficiently extend the coordinated mmw WLANs to be used for future 5th Generation (5G) cellular networks.Comment: 18 pages, 24 figures, accepted, invited paper

Cloud Cooperated Heterogeneous Cellular Networks for Delayed Offloading using Millimeter Wave Gates

Increasing the capacity of wireless cellular network is one of the major challenges for the coming years. A lot of research works have been done to exploit the ultra-wide band of millimeter wave (mmWave) and integrate it into future cellular networks. In this paper, to efficiently utilize the mmWave band while reducing the total deployment cost, we propose to deploy the mmWave access in the form of ultra-high capacity mmWave gates distributed in the coverage area of the macro basestation (Macro BS). Delayed offloading is also proposed to proficiently exploit the gates and relax the demand of deploying a large number of them. Furthermore, a mobility-aware weighted proportional fair (WPF) user scheduling is proposed to maximize the intra-gate offloading efficiency while maintaining the long-term offloading fairness among the users inside the gate. To efficiently link the mmWave gates with the Macro BS in a unified cellular network structure, a cloud cooperated heterogeneous cellular network (CC-HetNet) is proposed. In which, the gates and the Macro BS are linked to the centralized radio access network (C-RAN) via high-speed backhaul links. Using the concept of control/user (C/U) plane splitting, signaling information is sent to the UEs through the wide coverage Macro BS, and most of users’ delayed traffic is offloaded through the ultra-high capacity mmWave gates. An enhanced access network discovery and selection function (eANDSF) based on a network wide proportional fair criterion is proposed to discover and select an optimal mmWave gate to associate a user with delayed traffic. It is interesting to find out that a mmWave gate consisting of only 4 mmWave access points (APs) can offload up to 70 GB of delayed traffic within 25 sec, which reduces the energy consumption of a user equipment (UE) by 99.6 % compared to the case of only using Macro BS without gate offloading. Also, more than a double increase in total gates offloaded bytes is obtained using the proposed eANDSF over using the conventional ANDSF proposed by 3GPP due to the optimality in selecting the associating gate. 

Proactive Received Power Prediction Using Machine Learning and Depth Images for mmWave Networks

This study demonstrates the feasibility of the proactive received power prediction by leveraging spatiotemporal visual sensing information toward the reliable millimeter-wave (mmWave) networks. Since the received power on a mmWave link can attenuate aperiodically due to a human blockage, the long-term series of the future received power cannot be predicted by analyzing the received signals before the blockage occurs. We propose a novel mechanism that predicts a time series of the received power from the next moment to even several hundred milliseconds ahead. The key idea is to leverage the camera imagery and machine learning (ML). The time-sequential images can involve the spatial geometry and the mobility of obstacles representing the mmWave signal propagation. ML is used to build the prediction model from the dataset of sequential images labeled with the received power in several hundred milliseconds ahead of when each image is obtained. The simulation and experimental evaluations using IEEE 802.11ad devices and a depth camera show that the proposed mechanism employing convolutional LSTM predicted a time series of the received power in up to 500 ms ahead at an inference time of less than 3 ms with a root-mean-square error of 3.5 dB

A multi-traffic inter-cell interference coordination scheme in dense cellular networks

This paper proposes a novel semi-distributed and practical ICIC scheme based on the Almost Blank Sub-Frame (ABSF) approach specified by 3GPP. We define two mathematical programming problems for the cases of guaranteed and best-effort traffic, and use game theory to study the properties of the derived ICIC distributed schemes, which are compared in detail against unaffordable centralized schemes. Based on the analysis of the proposed models, we define Distributed Multi-traffic Scheduling (DMS), a unified distributed framework for adaptive interference-aware scheduling of base stations in future cellular networks, which accounts for both guaranteed and best-effort traffic. DMS follows a two-tier approach, consisting of local ABSF schedulers, which perform the resource distribution between the guaranteed and best effort traffic, and a light-weight local supervisor, which coordinates ABSF local decisions. As a result of such a two-tier design, DMS requires very light signaling to drive the local schedulers to globally efficient operating points. As shown by means of numerical results, DMS allows to: (i) maximize radio resources resue; (ii) provide requested quality for guaranteed traffic; (iii) minimize the time dedicated to guaranteed traffic to leave room for best-effort traffic; and (iv) maximize resource utilization efficiency for the best-effort traffic.The work of A. Banchs was supported by the H2020 5GMoNArch project (Grant Agreement No. 761445) and the 5GCity project of the Spanish Ministry of Economy and Competitiveness (TEC2016-76795-C6-3-R). The work of V. Mancuso has been supported by a Ramon y Cajal grant (ref: RYC-2014-16285) in part by the Spanish Ministry of Science, Innovation and Universities under grant TIN2017-88749-R and by the Madrid Regional Government through the TIGRE5-CM program (S2013/ICE-2919)

MM-Wave HetNet in 5G and beyond Cellular Networks Reinforcement Learning Method to improve QoS and Exploiting Path Loss Model

This paper presents High density heterogeneous networks (HetNet) which are the most promising technology for the fifth generation (5G) cellular network. Since 5G will be available for a long time, previous generation networking systems will need customization and updates. We examine the merits and drawbacks of legacy and Q-Learning (QL)-based adaptive resource allocation systems. Furthermore, various comparisons between methods and schemes are made for the purpose of evaluating the solutions for future generation. Microwave macro cells are used to enable extra high capacity such as Long-Term Evolution (LTE), eNodeB (eNB), and Multimedia Communications Wireless technology (MC), in which they are most likely to be deployed. This paper also presents four scenarios for 5G mm-Wave implementation, including proposed system architectures. The WL algorithm allocates optimal power to the small cell base station (SBS) to satisfy the minimum necessary capacity of macro cell user equipment (MUEs) and small cell user equipment (SCUEs) in order to provide quality of service (QoS) (SUEs). The challenges with dense HetNet and the massive backhaul traffic they generate are discussed in this study. Finally, a core HetNet design based on clusters is aimed at reducing backhaul traffic. According to our findings, MM-wave HetNet and MEC can be useful in a wide range of applications, including ultra-high data rate and low latency communications in 5G and beyond. We also used the channel model simulator to examine the directional power delay profile with received signal power, path loss, and path loss exponent (PLE) for both LOS and NLOS using uniform linear array (ULA) 2X2 and 64x16 antenna configurations at 38 GHz and 73 GHz mmWave bands for both LOS and NLOS (NYUSIM). The simulation results show the performance of several path loss models in the mmWave and sub-6 GHz bands. The path loss in the close-in (CI) model at mmWave bands is higher than that of open space and two ray path loss models because it considers all shadowing and reflection effects between transmitter and receiver. We also compared the suggested method to existing models like Amiri, Su, Alsobhi, Iqbal, and greedy (non adaptive), and found that it not only enhanced MUE and SUE minimum capacities and reduced BT complexity, but it also established a new minimum QoS threshold. We also talked about 6G researches in the future. When compared to utilizing the dual slope route loss model alone in a hybrid heterogeneous network, our simulation findings show that decoupling is more visible when employing the dual slope path loss model, which enhances system performance in terms of coverage and data rate

User Association and Enabling Technologies in Next Generation 5G Ultra-Dense Networks – A Review

Embedding small cells and relay nodes in a macro-cellular network is a promising method for achieving substantial gains in coverage and capacity compared to traditional macro only networks. These new types of base-stations can operate on the same wireless channel as the macro-cellular network, providing higher spatial reuse via cell splitting. However, these base-stations are deployed in an unplanned manner, can have very different transmit powers, and may not have traffic aggregation among many users. This could potentially result in much higher interference magnitude and variability. Hence, such deployments require the use of innovative cell association and inter-cell interference coordination techniques in order to realize the promised capacity and coverage gains. In this paper, we review various techniques for user association and interference mitigation which are required to meet increased data demand in next generation 5G ultra-dense networ