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Cloud- and fog-based PHY communications in 5G: performance, feedback and complexity

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30 personnes membres du GdR ISIS, et 39 personnes non membres du GdR, sont inscrits à cette réunion.
Capacité de la salle : 300 personnes.

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It is apparent that the evolution of mobile traffic in the last 5-6 years, indicates a growth that seems to be exponential. This can be attributed to a plethora of reasons, such as new devices that include smartphones, tablets, as well as to new attractive applications that include youtube, facebook, and network gaming.

There are indeed very good indications that this growth will continue as a result of demanding upcoming applications, such as machine type communications, drones, HQ video stream, etc.

This challenge to sustain this giant leap in volume and societal impact of wireless communications, has spurred worldwide research to produce radically new power-efficient high-performance environmentally-friendly communication technologies.

This GdR ISIS meeting, is directly motivated by these challenges, and will bring to the fore new ideas and paradigms in wireless communications, with special preference on works relating to massive MIMO, Cloud RAN, caching based techniques and edge-computing.

In the setting of Massive multiple-input multiple-output (MIMO), the idea is to equip base stations with a large number of antennas, in order to allow faster rates, higher spectral and energy efficiency, as well as to allow for simpler algorithms that benefit from the fact that large systems often converge to their deterministic limits. This relates somewhat to the concept of cloud RAN where now, a centralized entity controls transmissions from a large number of remote radio heads that can be closer to the users. In both these settings, which present their own opportunities and challenges, one can use the idea of anticipatory distributed caching that allows for predictably popular content to be placed closer to the users. All these ideas come together to give promise to a new way of communicating.

This workshop aims to be an ideal breeding ground not only to discuss technologies that are at the front end of the current vision for wireless networks but also to get inspiration and understanding of the plethora of ways they could inter-operate.

Call for participation:

Researchers that are interested in presenting their work in different related topics such as:

with emphasis on any of the following:

are invited to submit their proposal (title and abstract) via email to the organizers (elia@eurecom.fr and laura.cottatellucci@eurecom.fr) until the 7th of November 2015. In particular, the participation of PhD students working on these topics is highly encouraged.


Confirmed speakers:


8h50-9h20: Reception

9h20-9h30: Introduction

9h30-10h30: Giuseppe Caire (TU-Berlin)
Title: From Cloud to Fog: Massive MIMO, pCells, Cellular Interference Alignment, and Device-to-Device

10h30-11h10: Georgios Paschos (Huawei)
Title: Load Balancing in Cloud (and Fog) Computing

11h10-11h30: Dora Boviz (CentraleSupélec and Alcatel Lucent, Paris)
Title: C-RAN fronthaul enhancements using Software Defined Networking

11h30-12h10: Dirk Slock (EURECOM, Sophia Antipolis)
Sum Utility Optimization in MIMO Multi-User Multi-Cell: Centralized and Distributed, Perfect and Partial CSIT, Fast and Slow CSIT

12h10 - 13h40: Lunch Break

13h40-14h20: Iryna Andriyanova (ENSEA)
Repair Scheduling in Wireless Distributed Storage with D2D Communication

14h20-14h40: Laurent Roullet (Alcatel Lucent, Paris)

Title: CRAN challenges: the architecture and solutions in HARP

14h40-15h00: Qianrui LITBD (PhD student at XXX)

Title: Large System Analysis of Partially Centralized Networks

15h00-15h20: Coffee Break

15h20-16h00: Stefan Valentin (Huawei, Paris)
Title: Context-Aware and Anticipatory Resource Management for the 5G RAN

16h00 - 16h20: Ejder Bastug (CentraleSupélec, Paris)

Big Data Meets Telcos: A Proactive Caching Perspective

Résumés des contributions

From Cloud to Fog: Massive MIMO, pCells, Cellular Interference Alignment, and Device-to-Device

Speaker: Giuseppe Caire (TU-Berlin)

Abstract: In this talk, we review a number of recent results on candidate disruptive wireless technologies which may become (or inspire) components of the forthcoming 5th Generation of wireless/cellular systems.

We start with reviewing the by now well-known massive MIMO approach, based on a large number of co-located antennas at the infrastructure side, and joint processing thereof. Then, we move to a distributed placement of antennas, albeit with some form of joint processing in clusters. Then, we shall present a recent approach based on local decoding and local message passing, enabling network-wide one-shot interference alignment, i.e., without requiring highly impractical alignment precoding based on symbol extension (a' la Cadambe and Jafar) and/or signal level resolution(the so-called ``real'' interference alignment). Finally, we shall present some recent results on a completely decentralized device-to-device network, where coordination between users is only at the level of link scheduling and power control, and yet the network can operate in a very attractive regime despite interference is treated as Gaussian noise.

While it is hard to make fair comparisons between these approaches, it is interesting to notice that each one of them has pros and cons, and often the balancing of these aspects requires a more in-depth system evaluation than the clean and elegant, but necessarily idealized, information theoretic analysis. Hence, which degree of cloud and fog a good system architecture should have is yet an open and interesting debate.

Load Balancing in Cloud (and Fog) Computing

Speaker: Georgios Paschos (Huawei)

Abstract: The talk is comprised of two parts. In the first part I will discuss new fairness notions in the domain of balancing load. In particular, a connection between penalty minimization of convex functions is made to penalty fairness notions (weighted min-max fairness and most balanced allocations). Through an example with job execution in servers, it is showcased that such fairness metrics can be used to reduce delays during traffic peaks. Penalty fairness is a very useful tool for the domain of Cloud (and Fog) Computing.

In the second part of the talk I will focus on the problem of distributed computation over a network. Queries arrive in the system for data that are stored in remote locations. The data need to be communicated to computation nodes, be processed and then finally delivered to the destination. In the wireless Cloud (and Fog) computing environment, nodes may be mobile and the traffic may be unknown. We design a distributed dynamic algorithm for this schema. The algorithm combines load balancing, routing (and scheduling of wireless links), and it is shown to sustain the maximum rate of queries.

C-RAN fronthaul enhancements using Software Defined Networking

Speaker: Dora Boviz (CentraleSupélec and Alcatel-Lucent, Paris)

Abstract: Cloud Radio Access Networks (C-RAN) offer numerous advantages both on the functional and the hardware plane. We can efficiently control the access network using Software Defined Networking, but it is not the only benefit of SDN technology. Optimization of various network features and elements can be done by plug-and-play applications interfaced with the SDN controller. Since it orchestrates all the network elements from Remote Radio Heads (RRHs) to the Baseband Unit (BBU) pool, which all provide real-time measurements that can be then used by optimization algorithms. In the talk, we present SDN enabled C-RAN architecture and its advantages for network control, then we focus on various features that it facilitates. These can impact wireless transmissions (e.g. eICIC, Network MIMO), fronthaul network (e.g. routing over Ethernet fronthaul) or computational resources (e.g. load balancing). We would like to highlight how SDN allows scalable and reconfigurable realization of these features and how it can improve them with respect to Distributed RAN or centralized architectures without collective control over network elements.

Sum Utility Optimization in MIMO Multi-User Multi-Cell: Centralized and Distributed, Perfect and Partial CSIT, Fast and Slow CSIT

Speaker: Dirk Slock (EURECOM)

Abstract: The Interfering Broadcast Channel (IBC) applies to the downlink of multi-cell networks, which are limited by multi-user (MU) interference. The interference alignment (IA) concept has shown that interference does not need to be inevitable. In particular spatial IA in the MIMO IBC allows for low latency. However, IA requires perfect and typically global Channel State Information at the Transmitter(s) (CSIT), whose acquisition does not scale well with network size. Also, the design of transmitters (Txs) and receivers (Rxs) is coupled and hence needs to be centralized (cloud) or duplicated (distributed approach). We first consider two popular approaches for centralized designs with full CSIT: linking Weighted Sum rate (WSR) to Weighted Sum MSE (WSMSE) and the Differenc e of Convex functions (DC programming) approaches. We furthermore explore a relation between the WSMSE and DC approaches, indicating significant convergence speed potential for the latter. Through simulated annealing, IA solutions shed light on local and global WSR optima. However, CSIT, which is crucial in multi-user systems, is always imperfect in practice. We consider mean and covariance Gaussian partial CSIT, and the special case of a (possibly location based) MIMO Ricean channel model. We focus on the optimization of beamformers for the expected weighted sum rate (EWSR) under per BS power constraints by extending the perfect CSI techniques. We then focus on distributed techniques that exploit local CSIT, feedback of a limited number of scalars, and only one or few iterations. In particular we propose an approach that focuses on the (dominant) multipath components in the MIMO propagation channels with only the slow fading components known to the Tx, corresponding to a structured form of covariance CSIT. The pathwise approach allows for a decomposition of the alignment tasks between Tx and Rx, leading to the sufficiency of local pathwise CSIT plus limited coordination overhead. To optimize EWSR at finite SNR, we exploit the uplink/downlink duality to design the Tx beamformers as MMSE filters, in which averaging over complex path amplitudes leads to optimized pathwise interference limitation. We furthermore explore a relation between the difference of convex (DC) functions programming and the Weighted Sum MSE (WSMSE) approaches, indicating significant convergence speed potential for the former, and allowing a fixing of the latter for the case of partial CSIT.

Repair Scheduling in Wireless Distributed Storage with D2D Communication

Speaker: Iryna Andriyanova (ETIS, UMR8051, ENSEA / Univ. Cergy-Pontoise / CNRS)

Abstract: We consider distributed storage (DS) for a wireless network where mobile devices arrive and depart according to a Poisson random process. Content is stored in a number of mobile devices, using an erasure correcting code. When requesting a piece of content, a user retrieves the content from the mobile devices using device-to-device communication or, if not possible, from the base station (BS), at the expense of a higher communication cost. We consider the repair problem when a device that stores data leaves the network. In particular, we introduce a repair scheduling where repair is performed (from storage devices or the BS) periodically. We derive analytical expressions for the overall communication cost of repair and download as a function of the repair interval. We illustrate the analysis by giving results for maximum distance separable codes, regenerating codes and locally repairable codes. Our results show that DS can reduce the overall communication cost with respect to the case where content is only downloaded from the BS, provided that repairs are performed frequently enough. The required repair frequency depends on the code used for storage and the network parameters. In particular, the required repair frequency decreases with increasing request rate and increases with decreasing BS communication cost. Also, involving more mobile devices in the repair necessitates that we repair the wireless DS more frequently. Furthermore, we show that the repair interval that minimizes the total communication cost depends on the code and network parameters. Instantaneous repair is not always the optimal solution. Finally, given a repair interval and a set of network parameters, we suggest code families that will achieve the minimum communication cost.

CRAN challenges: the architecture and solutions in HARP

Speaker: Laurent Roullet (Alcatel-Lucent)

Abstract: One important challenge in cellular networks is the ability to face "exponential" demand that can be addressed by active antenna systems with larger MIMO modes and denser cell distributions. To support this scalability, the HARP architecture focuses on joint design of centralized cloud RAN architecture and load-controlled antenna arrays. The remaining bottleneck is therefore the stringent fronthaul requirements in terms of bandwidth, jitter and latency. We will illustrate how these requirements have been relaxed in the HARP project without (too much) impairments.

Large System Analysis of Partially Centralized Networks

Speaker: Qianrui LI (EURECOM)

Abstract: Cloud-based cooperative MIMO promises large performance increase through the cancellation of interferences using global channel state information in the cloud. However, a perfect centralization of CSI is not always be possible due to backhaul exchange imperfections (noise, quantization, fading outdating), such that methods that are robust to a partial (or full) decentralization of the CSI become an interesting solution. In this talk, we analyze the performance in such settings when the number of antennas at each transmitter becomes large (e.g. massive arrays) and the CSI is arbitrarily imperfectly shared between the transmitters. We assess the degradation of conventional precoding schemes and we discuss how to make cooperative transmission more robust to imperfect CSI sharing.

Context-Aware and Anticipatory Resource Management for the 5G RAN

Speaker: Stefan Valentin (Huawei)

Abstract: Operators, vendors and academia have recognized the tremendous potential of large datasets in order to achieve the challenging requirements of future Radio Access Networks (RANs). It is now evident that ?Big Data? provides deep insight in RAN operation, leads to new operation paradigms, and enables a degree of optimization that goes far beyond the reactive and self-centered operation of wireless networks today. This talk will introduce two new operation concepts that are enabled by ?Big Data?: Context-Aware and Anticipatory Communications. We will discuss the exploitation of user context, such as location, propagation environment and application constraints as well as the construction and usage of large radio maps. We will then demonstrate the use of this data for channel prediction and anticipatory resource allocation from the perspective of Bayesian spatio-temporal inference, Support Vector Machines, adaptive filters and linear programming. After presenting impressive spectral efficiency gains at high service quality, we will conclude with architecture and standardization requirements for providing truly seamless service with 5G.

Big Data Meets Telcos: A Proactive Caching Perspective

Speaker: Ejder Bastug (CentraleSupélec, Paris)

Abstract: Mobile cellular networks are becoming increasingly complex to manage while classical deployment/optimization techniques and current solutions (i.e., cell densification, acquiring more spectrum, etc.) are cost-ineffective and thus seen as stopgaps. This calls for development of novel approaches that leverage recent advances in storage/memory, context-awareness, edge/cloud computing, and falls into framework of big data. However, the big data by itself is yet another complex phenomena to handle and comes with its notorious 4V: velocity, voracity, volume and variety. In this work, we address these issues in optimization of 5G wireless networks via the notion of proactive caching at the base stations. In particular, we investigate the gains of proactive caching in terms of backhaul offloadings and request satisfactions, while tackling the large-amount of available data for content popularity estimation. In order to estimate the content popularity, we first collect users' mobile traffic data from a Turkish telecom operator from several base stations in hours of time interval. Then, an analysis is carried out locally on a big data platform and the gains of proactive caching at the base stations are investigated via numerical simulations. It turns out that several gains are possible depending on the level of available information and storage size. For instance, with 10% of content ratings and 15.4 Gbyte of storage size (87% of total catalog size), proactive caching achieves 100% of request satisfaction and offloads 98% of the backhaul when considering 16 base stations.

Date : 2015-11-20

Lieu : Telecom ParisTech, amphi Thévenin

Thèmes scientifiques :
D - Télécommunications : compression, protection, transmission

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