Throughput-optimal Resource Allocation in LTE-Advanced with Distributed Antennas

Distributed antennas are envisaged for LTE-Advanced deployments in order to improve the coverage and increase the cell throughput. The latter in turn depends on how resources are allocated to the User Equipments (UEs) at the MAC layer. In this paper we discuss how to allocate resources to UEs so as to maximize the cell throughput, given that UEs may re-ceive from several antennas simultaneously. We first show that the problem is both NP-hard and APX-hard, i.e. no polynomial-time algorithm exists that approximates the opti-mum within a constant factor. Hence, we pro-pose and evaluate two polynomial-time heuristics whose complexity is feasible for practical purposes. Our simulative analysis shows that, in practical scenarios, the two heuristics are highly accurate

Scalability and energy efficiency of Coordinated Scheduling in cellular networks towards 5G

Coordinated Scheduling (CS) is one of the main techniques to control inter-cell interference in present (4G) and future (5G) cellular networks. We show that coordination of a cluster of nodes can be formulated as an optimization problem, i.e., placing the Resource Blocks in each node’s subframe with the least possible overlapping with neighboring nodes. We provide a clever formulation, which allow optimal solutions to be computed in clusters of ten nodes, and algorithms that compute good suboptimal solutions for clusters of several tens of nodes, fast enough for a network to respond to traffic changes in real time. This allows us to assess the relationship between the scale at which CS is performed and its benefits in terms of network energy efficiency and cell-edge user rate. Our results show that optimal CS allows a significant protection of cell-edge users. Moreover, this goes hand-in-hand with a significant reduction in the number of allocated Resource Blocks, which in turn allows an operator to reduce its energy consumption. Both benefits actually increase with the size of the clusters

A testbed for flexible and energy-efficient resource management with virtualized LTE-A nodes

This paper describes the software architecture and the implementation of a fully operational testbed that demonstrates the benefits of flexible, dynamic resource allocation with virtualized LTE-A nodes. The testbed embodies and specializes the general software architecture devised within the Flex5Gware EU project, and focuses on two intelligent programs: the first one is a Global Scheduler, that coordinates radio resource allocation among interfering nodes; the second one is a Global Power Manager, which switches on/off nodes based on their expected and measured load over a period of minutes. The software framework is written using open-source software, and includes fast, scalable optimization algorithms at both components. Moreover, it supports virtualized BaseBand Units, implemented using OpenAir-Interface, that can run on physical and virtual machines. We present the results obtained via on-field measurements, that demonstrate the feasibility and benefits of our approach

Flexible dynamic Coordinated Scheduling in Virtual-RAN deployments

Using Coordinated Scheduling (CS), eNodeBs in a cellular network dynamically agree on which Resource Blocks (not) to use, so as to reduce the interference, especially for celledge users. This paper describes a software framework that allows dynamic CS to occur among a relatively large number of nodes, as part of a more general framework of network management devised within the Flex5Gware project. The benefits of dynamic CS, in terms of spectrum efficiency and resource saving, are illustrated by means of simulation and with live measurements on a prototype implementation using virtualized eNodeBs

Throughput-optimal Resource Allocation in LTE-Advanced with Distributed Antennas

Distributed antennas are envisaged for LTEAdvanced deployments in order to improve the coverage and increase the cell throughput. The latter in turn depends on how resources are allocated to the User Equipments (UEs) at the MAC layer. In this paper we discuss how to allocate resources to UEs so as to maximize the cell throughput, given that UEs may receive from several antennas simultaneously. We first show that the problem is both NPhard and APX-hard, i.e. no polynomial-time algorithm exists that approximates the optimum within a constant factor. Hence, we propose and evaluate two polynomial-time heuristics whose complexity is feasible for practical purposes. Our simulative analysis shows that, in practical scenarios, the two heuristics are highly accurate

LTE scheduling

A method executed in a wireless communication network including at least one base station associated to a corresponding area transmitting/receiving data to/from corresponding user terminals located within the area. The method generates a user-rate matrix for each base station. Each element of the user-rate matrix provides a corresponding score, in terms of achievable rate, to a user terminal or group of user terminals within the corresponding area when a transmission is made to/from the user terminal or group of user terminals, respectively, from/to the base station by employing a selected transmission mode. The method further processes the elements of the user-rate matrix to create a scheduling list sorting the elements by a decreasing score, and associating to each user terminal a corresponding selected transmission mode based on the scheduling list for the transmission/reception of data to/from the base station

Scheduling Algorithm for Wireless Communication Networks

A method scheduling resources allocation within a wireless communications network including at least one network cell including a central unit providing coverage over the network cell and managing at least one transmission frame for putting the central unit into communication with at least one user equipment. The method includes: retrieving input parameters including, for each user equipment, a channel quality parameter indicating a measured/estimated channel quality based on actual network cell conditions; applying a de-contextualization function to each channel quality parameter for obtaining a corresponding atomic channel quality parameter indicating channel quality de-contextualized from the actual network cell conditions; performing a scheduling algorithm providing a binary allocation matrix indicating each scheduled physical resource block, transmission frame and user equipment; and applying a contextualization function to the allocation matrix obtaining transport block size data usable by the scheduled transmission frame for transport blocks transmissions from or towards each scheduled user equipment

EuQoS: End-to-End Quality of Service over Heterogeneous Networks

The EuQoS (End-to-End QoS over Heterogeneous Networks) IST Integrated European Project aimed to define a Next Generation Network architecture that builds, uses and manages end-to-end QoS across different administrative domains and heterogeneous networks (UMTS, xDSL, Ethernet, WiFi, Satellite and IP/MPLS). The EuQoS architecture preserves the openness and the decentralized decision model of the actual Internet, runs on off-the-shelf hardware and network equipment, and allows end users to request various services without changing the Application Signaling protocol, while meeting regulators’ and users’ Net Neutrality requirements. This paper presents the key elements of the EuQoS architecture and describes the main results obtained in field trials performed on a fully-functional EuQoS system prototype developed over a pan-European testbed. Furthermore, the paper discusses the main strengths of the system and the issues related to its actually deployment on a large scale, from both technical and market points of view