92 research outputs found

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

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    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

    Opportunistic Spatial Preemptive Scheduling for URLLC and eMBB Coexistence in Multi-User 5G Networks

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    DR9.3 Final report of the JRRM and ASM activities

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    Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version

    Radio Resource Management for Ultra-Reliable Low-Latency Communications in 5G

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    A survey of self organisation in future cellular networks

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    This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

    Adaptive scheduling in cellular access, wireless mesh and IP networks

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    Networking scenarios in the future will be complex and will include fixed networks and hybrid Fourth Generation (4G) networks, consisting of both infrastructure-based and infrastructureless, wireless parts. In such scenarios, adaptive provisioning and management of network resources becomes of critical importance. Adaptive mechanisms are desirable since they enable a self-configurable network that is able to adjust itself to varying traffic and channel conditions. The operation of adaptive mechanisms is heavily based on measurements. The aim of this thesis is to investigate how measurement based, adaptive packet scheduling algorithms can be utilized in different networking environments. The first part of this thesis is a proposal for a new delay-based scheduling algorithm, known as Delay-Bounded Hybrid Proportional Delay (DBHPD), for delay adaptive provisioning in DiffServ-based fixed IP networks. This DBHPD algorithm is thoroughly evaluated by ns2-simulations and measurements in a FreeBSD prototype router network. It is shown that DBHPD results in considerably more controllable differentiation than basic static bandwidth sharing algorithms. The prototype router measurements also prove that a DBHPD algorithm can be easily implemented in practice, causing less processing overheads than a well known CBQ algorithm. The second part of this thesis discusses specific scheduling requirements set by hybrid 4G networking scenarios. Firstly, methods for joint scheduling and transmit beamforming in 3.9G or 4G networks are described and quantitatively analyzed using statistical methods. The analysis reveals that the combined gain of channel-adaptive scheduling and transmit beamforming is substantial and that an On-off strategy can achieve the performance of an ideal Max SNR strategy if the feedback threshold is optimized. Finally, a novel cross-layer energy-adaptive scheduling and queue management framework EAED (Energy Aware Early Detection), for preserving delay bounds and minimizing energy consumption in WLAN mesh networks, is proposed and evaluated with simulations. The simulations show that our scheme can save considerable amounts of transmission energy without violating application level QoS requirements when traffic load and distances are reasonable

    Multi-Service Radio Resource Management for 5G Networks

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    Operating multi-user transmission for 5G and beyond cellular systems

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    Every decade, a new generation of cellular networks is released to keep up with the ever-growing demand for data and use cases. Traditionally, cellular networks rely on partitioning radio resources into a set of physical resource blocks (PRBs). Each PRB is used by the base-station to transmit exclusively to one user, which is referred to as single-user transmission. Recently, multi-user transmission has been introduced to enable the base-station to simultaneously serve multiple users using the same PRB. While multi-user transmission can be much more efficient than its single-user counterpart, it is significantly more challenging to operate. Thus, in this thesis we study the operation, i.e., the Radio Resource Management (RRM), for two popular multi-user transmission technologies; namely, 1) Non-Orthogonal Multiple Access (NOMA) and 2) Multi-User Multiple-Input Multiple-Output (MU-MIMO). For NOMA RRM, we study a multi-cell, multi-carrier downlink system. First, we formulate and solve a centralized proportional fair scheduling genie problem that jointly performs user selection, power allocation and power distribution, and Modulation and Coding Scheme (MCS) selection. While such a centralized schedule is practically infeasible, it upper bounds the achievable performance. Then, we propose a simple static coordinated power allocation scheme across all cells for NOMA using a simple power map that is easily calibrated offline. We find that using a simple static coordinated power allocation scheme improves performance by 80% compared to equal power allocation. Finally, we focus on online network operation and study practical schedulers that perform user-selection, power distribution, and MCS selection. We propose a family of practical scheduling algorithms, each of them exhibiting a different trade-off between complexity (i.e., run-time) and performance. The one we selected sacrifices a maximum of 10% performance while reducing the computation time by a factor of 45 with respect to the optimal user scheduler. For MU-MIMO RRM, we focus on the study of the downlink of an OFDMA massive MU-MIMO single cell assuming ZFT (Zero Forcing Transmission) precoding. An offline study is initiated with the goal of finding the best achievable performance by jointly optimizing user-selection, power distribution and MCS selection. The best performance is analyzed by using both Branch-Reduce-and-Bound (BRB) global optimization technique for upper-bounding the achievable performance and a set of different greedy searches for lower bounding the achievable performance to find good feasible solutions. The results suggest that a specific search strategy referred to as greedy-down-all-the-way (GDAW) with full-drop (FD) is quasi-optimal. Afterwards, we design a simple practical scheduler that achieves 97% of the performance to GDAW with FD and has comparable runtime to that of the state-of-the-art benchmark that selects all users, performs ZFT precoding followed by power distribution using water-filling. The proposed scheme performs a simple round robin grouping to select users, followed by ZFT precoding and joint power distribution and MCS selection via a novel greedy algorithm with a possible additional iteration to take zero-rate users into account. Our solution outperforms the benchmark by 281%
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