Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Initial Access in 5G mm-Wave Cellular Networks

The massive amounts of bandwidth available at millimeter-wave frequencies (roughly above 10 GHz) have the potential to greatly increase the capacity of fifth generation cellular wireless systems. However, to overcome the high isotropic pathloss experienced at these frequencies, high directionality will be required at both the base station and the mobile user equipment to establish sufficient link budget in wide area networks. This reliance on directionality has important implications for control layer procedures. Initial access in particular can be significantly delayed due to the need for the base station and the user to find the proper alignment for directional transmission and reception. This paper provides a survey of several recently proposed techniques for this purpose. A coverage and delay analysis is performed to compare various techniques including exhaustive and iterative search, and Context Information based algorithms. We show that the best strategy depends on the target SNR regime, and provide guidelines to characterize the optimal choice as a function of the system parameters.Comment: 6 pages, 3 figures, 3 tables, 15 references, submitted to IEEE COMMAG 201

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

ATM-based TH-SSMA network for multimedia PCS

Personal communications services (PCS) promise to provide a variety of information exchanges among users with any type of mobility, at any time, in any place, through any available device. To achieve this ambitious goal, two of the major challenges in the system design are: i) to provide a high-speed wireless subsystem with large capacity and acceptable quality-of-service (QoS) and ii) to design a network architecture capable of supporting multimedia traffic and various kinds of user mobility. A time-hopping spread-spectrum wireless communication system called ultra-wide bandwidth (UWB) radio is used to provide communications that are low power, high data rate, fade resistant, and relatively shadow free in a dense multipath environment. Receiver-signal processing of UWB radio is described, and performance of such communications systems, in terms of multiple-access capability, is estimated under ideal multiple-access channel conditions. A UWB-signal propagation experiment is performed using the bandwidth in excess of 1 GHz in a typical modern office building in order to characterize the UWB-signal propagation channel. The experimental results demonstrate the feasibility of the UWB radio and its robustness in a dense multipath environment. In this paper, an ATM network is used as the backbone network due to its high bandwidth, fast switching capability, flexibility, and well-developed infrastructure. To minimize the impact caused by user mobility on the system performance, a hierarchical network-control architecture is postulated. A wireless virtual circuit (WVC) concept is proposed to improve the transmission efficiency and simplify the network control in the wireless subsystem. The key advantage of this network architecture and WVC concept is that the handoff can be done locally most of the time, due to the localized behavior of PCS users.published_or_final_versio