Radio Resource Management

In this paper, we propose fairness-oriented packet scheduling (PS) schemes with power-efficient control mechanism for future packet radio systems. In general, the radio resource management  functionality plays an important role in new OFDMA based networks. The control of the network resource division among the users is performed by packet scheduling functionality based on maximizing cell coverage and capacity satisfying, and certain quality of service requirements. Moreover, multi-antenna transmit-receive schemes provide additional flexibility to packet scheduler functionality. In order to mitigate inter-cell and co-channel interference problems in OFDMA cellular networks soft  frequency reuse with different power masks patterns is used. Stemming from the earlier enhanced  proportional fair scheduler studies for single-input multiple-output (SIMO) and multiple-input multiple-output (MIMO) systems, we extend the development of efficient packet scheduling algorithms by adding transmit power considerations in the overall priority metrics calculations and scheduling decisions. Furthermore, we evaluate the proposed scheduling schemes by simulating practical orthogonal frequency division multiple access (OFDMA) based packet radio system in terms of throughput, coverage and  fairness distribution among users. In order to completely reveal the potential of the proposed schemes we investigate the system performance of combined soft frequency reuse schemes with advanced power-aware packet scheduling algorithms for further optimization. As a concrete example, under reduced overall transmit power constraint and unequal power distribution for different sub-bands, we demonstrate that by using the proposed power-aware multi-user scheduling schemes, significant coverage and fairness improvements in the order of 70% and 20%, respectively, can be obtained, at the expense of average throughput loss of only 15%.

Two main draft standards were submitted in October 2009 as candidate technologies for IMT-Advanced, namely IEEE 802.16m and 3GPP LTE-Advanced. However, several details on their functionalities are still open and the research community is racing towards the complete definition of the revolutionary next fourth generation mobile, 4G. In this framework the European Celtic project WINNER+ is bridging together experts from industry, academia and government all around Europe to devise these 4G technologies. This paper presents the second part of innovative concepts for advanced Radio Resource Management that has been identified by the Innovation Group of WINNER+ for potential inclusion in IMT-Advanced. These concepts consist of promising innovative techniques that are ready to be included in current OFDMA-based cellular systems to enhance system performance. A brief description of each technique together with the relevant state of the art is provided.

In this paper, we propose, implement, and test two novel downlink LTE scheduling algorithms. The implementation and testing of these algorithms were in Matlab, and they are based on the use of Reinforcement Learning (RL), more specifically, the Q-learning technique for scheduling two types of users. The first algorithm is called a Collaborative scheduling algorithm, and the second algorithm is called a Competitive scheduling algorithm. The first type of the scheduled users is the Primary Users (PUs), and they are the licensed subscribers that pay for their service. The second type of the scheduled users is the Secondary Users (SUs), and they could be un-licensed subscribers that don't pay for their service, device-to-device communications, or sensors. Each user whether it’s a primary or secondary is considered as an agent. In the Collaborative scheduling algorithm, the primary user agents will collaborate in order to make a joint scheduling decision about allocating the resource blocks to each one of them, then the secondary user agents will compete among themselves to use the remaining resource blocks. In the Competitive scheduling algorithm, the primary user agents will compete among themselves over the available resources, then the secondary user agents will compete among themselves over the remaining resources. Experimental results show that both scheduling algorithms converged to almost 90% utilization of the spectrum, and provided fair shares of the spectrum among users.

This deliverable presents a literature survey of localisation in communication networks. In a first part, use of communication networks for location estimation is presented. Two families of methods do exist: fingerprinting and geometrical techniques. Cooperative positioning is one possible enhancement. In a second part, use of location information to improve radio resource management, specifically handover decision and relay selection, is

This paper focuses on an essential task of the enhanced NodeB eNodeB element in LTE architecture, the
Radio Resource Manager RRM, which aims to accept or reject requests for connection to the network
based on some constraints and ensuring optimal distribution of radio resources between Users Equipments
UEs. Its main functionalities include Admission Control AC and Packet Scheduling PS.
This paper will center mainly on the PS part of the RRM task, which performs the radio resource
allocation in both uplink and downlink directions. Several approaches and algorithms have been proposed
in the literature to address this need (allocate resources efficiently), the diversity and multitude of
algorithms is related to the factors considered for the optimal management of radio resource, specifically,
the traffic type and the QoS (Quality of Service) requested by the UE.
In this article, an art’s state of the radio resource allocation strategies and a detailed study of several
scheduling algorithms proposed for LTE (uplink and downlink) are made. Therefore, we offer our
evaluation and criticism.

Deployment of heterogeneous wireless networks is spreading throughout the world as users want to be connected anytime, anywhere, and anyhow. Meanwhile, these users are increasingly interested in multimedia applications such as video streaming and Voice over IP (VoIP), which require strict Quality of Service (QoS) support. Provisioning network resources with such constraints is a challenging task. In fact, considering the

— The 3 rd Generation Partnership Project (3GPP) introduced Long Term Evolution (LTE) in release 8, and afterwards it was updated significantly in later releases (referred to as LTE-Advanced). LTE and LTE-Advanced (LTE-A) aim to achieve higher spectral efficiency, higher data rates, robustness and flexibility. Intelligent channel-aware radio resource scheduling is one of the key features of LTE-A. A number of schedulers proposed in the literature rely on the feedback sent from the Users Equipment (UE) without considering the presence of feedback delay. In this paper, we analyse the effect of the uplink delay on the cell performance of existing schedulers, in terms of throughput and the users' fairness. We then propose an adaptive hybrid scheduler to overcome the effect of the uplink delay on the scheduler performance. The simulation results show that our proposed scheduling algorithm outperforms the existing schedulers in the presence of uplink feedback delay.

In recent years several wireless communication standards have been developed and more are expected, each with different scope in terms of spatial coverage, radio access capabilities, and mobility support. Heterogeneous networks combine multiple of these radio interfaces both in network infrastructure and in user equipment which requires a new multi-radio framework, enabling mobility and handover management for multiple RATs. The

This paper highlights an algorithm for detecting the presence of wireless signal using the Singular Value Decomposition (SVD) technique. We simulated the algorithm to detect common digital signals in wireless communication to test the performance of the signal detector. The SVD-based signal detector was found to be more efficient in detecting a signal without knowing the properties of the transmitted signal. The performance of the algorithm is better compared to the favorable energy detection. The algorithm is suitable for blind spectrum sensing where the properties of the signal to be detected are unknown. This is also the advantage of the algorithm since any signal would interfere and subsequently affect the quality of service (QoS) of the IEEE 802.22 connection.

The provision of very high data rates in a ubiquitous manner throughout the service area is a great challenge for 4G and beyond-4G wireless networks. Towards that end, the deployment of fixed relays by the operators has become an accepted radio access network concept in various standardization activities including LTE-A and 802.16j. It is envisaged that next-generation networks will comprise a plethora of wireless relay stations. Worthy of mention is the plug-and-play type of relay known as nomadic relay. We devise novel radio resource management (RRM) schemes to facilitate the operation of fixed relay stations (FRSs) and nomadic relay stations (NRSs) in OFDMA-based multicellular networks. Two schemes of different decentralization levels are devised and classified as distributed and semi-centralized. A novel user-based dynamic routing or link selection that significantly reduces the feedback overhead is employed. We develop methods by which the NRSs act autonomously to acquire radio resources without relying on a central entity. NRS operation is the same in the two schemes and can be extended to any other OFDMA-based RRM scheme. Through the asynchronous opportunistic medium access of the NRSs, smart and opportunistic intra-cell channel reuse is attained. This is different from the static intra-cell reuse patterns often adopted in literature. Furthermore, we introduce a method to enable the cooperation between an NRS and a serving FRS to assist a troubled wireless terminal (WT). We thus establish the concept of nomadic relay-augmented fixed relay networks. To the extent of our knowledge of the literature, no other work has undertaken this task so far.

Abstract: This Deliverable, D6. 1, reports the results of Task 6.1 which addresses the development of dynamic radio resource management algorithms for an efficient use of TVWS. In this context, the overall objective of D6. 1 is to design, simulate and evaluate a TVWS allocation mechanism, able to be adopted in spectrum broker entity of COGEU demonstrator. Towards this main objective, an overall TVWS allocation process is proposed including matching optimization and spectrum auction. The evaluation results validated ...

Hierarchical Genetic Algorithms (HGA) as a tool for search and optimizing methodology have now reached a mature stage. The minimum resource facility to carry user traffic, termed a channel unit (CU), is composed of a one time-slot and one code in the TD-CDMA/TDD system. The control of the number of CUs depends on the traffic load solves varied and asymmetrical traffic problems in the 3G system. In a cellular network, the call arrival rate, call duration and the communication overhead between the base stations and the control center are vague and uncertain, regardless of whether the criteria of concern are nonlinear, constrained, discrete or NP hard. In this paper, the HGA is used to tackle the neural network (NN) topology as well as the fuzzy logic controller for the dynamic CU allocation scheme in wireless cellular networks. Therefore, we propose a new efficient HGA CUs Allocation (HGACA) in cellular networks. It aims to efficiently satisfy the diverse quality-of-service (QoS) requirements of multimedia traffic. The results show our algorithm has a lower blocking rate, lower dropping rate, less update overhead, and shorter channel-acquisition delay than previous methods.

Underlaying Device-to-Device (D2D) communications can increase the spectral efficiency of cellular networks when sharing part of the spectrum with cellular users. This requires radio resource allocation policies capable to limit and control the interference between D2D and cellular communications. Many of the proposed policies are centralized, and require the base station to decide which resources should be allocated to each D2D transmission. Centralized schemes can efficiently control interference levels, but their feasibility can be compromised by their complexity and signaling overhead. To address this constraint, this paper proposes DiRAT, a distributed radio resource allocation scheme for D2D communications underlaying cellular networks. With DiRAT, the D2D nodes locally select their radio resources from a pool created by the cellular network in order to control the interference generated to the primary cellular users. DiRAT includes a control mechanism to ensure that the user QoS requirements are satisfied. This study demonstrates that DiRAT can increase the network capacity while avoiding or limiting the degradation of the performance of the primary cellular users. DiRAT also significantly reduces the complexity and overhead compared to existing centralized and distributed schemes.

Device-to-Device (D2D) communications can increase the spectral efficiency of future cellular networks when sharing part of the cellular spectrum. Radio resource allocation mechanisms are then necessary to control the interference that D2D and cellular transmissions can generate to each other. Most of the existing allocation schemes rely on the knowledge of the channel gain of all possible links between cellular and D2D nodes. This paper proposes to reduce the complexity cost and signalling overhead of the allocation process by using location information available at the network level. Using this information, the base station assigns radio resources to new D2D transmissions with the objective to control and limit the interference to the primary cellular users and existing D2D transmissions. The proposed radio resource allocation scheme continuously monitors that the user QoS requirements are satisfied. If it is not the case, it dynamically modifies the resource allocation to the interfering D2D transmissions. The proposed scheme achieves performance levels similar to that obtained with an optimized centralized allocation scheme, but with a significantly lower complexity cost and signaling overhead.

Radio resource management mechanisms in current and future wireless networks is expected to face an enormous challenge due to the ever increasing demand for bandwidth and latency sensitive applications on mobile devices. This is because an optimal resource allocation scheme which attempts to multiplex the available bandwidth in order to maximize Quality of service (QoS), will pose an exponential computational burden at eNodeB. In order to minimize such computational overhead, this work proposes a hybrid offline-online resource allocation strategy which effectively allocates all the available resources among flows such that their QoS requirements are satisfied. The flows are firstly classified into priority buckets based on real-time criticality factors. During the offline phase, the scheduler attempts to maintain the system load within a pre-specified safe threshold value by selecting an appropriate number of buckets. This offline selection procedure makes use of supervisory control theory of discrete event systems to synthesize an offline scheduler. Next, we have devised an online resource allocation strategy which runs on top of the offline policy and attempts to minimize the impact of the inherent variability in wireless networks. Simulation results show that the proposed scheduling framework is able to provide satisfactory QoS to all end users in most practical scenarios.