58 research outputs found

    Echo State Learning for Wireless Virtual Reality Resource Allocation in UAV-enabled LTE-U Networks

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    In this paper, the problem of resource management is studied for a network of wireless virtual reality (VR) users communicating using an unmanned aerial vehicle (UAV)-enabled LTE-U network. In the studied model, the UAVs act as VR control centers that collect tracking information from the VR users over the wireless uplink and, then, send the constructed VR images to the VR users over an LTE-U downlink. Therefore, resource allocation in such a UAV-enabled LTE-U network must jointly consider the uplink and downlink links over both licensed and unlicensed bands. In such a VR setting, the UAVs can dynamically adjust the image quality and format of each VR image to change the data size of each VR image, then meet the delay requirement. Therefore, resource allocation must also take into account the image quality and format. This VR-centric resource allocation problem is formulated as a noncooperative game that enables a joint allocation of licensed and unlicensed spectrum bands, as well as a dynamic adaptation of VR image quality and format. To solve this game, a learning algorithm based on the machine learning tools of echo state networks (ESNs) with leaky integrator neurons is proposed. Unlike conventional ESN based learning algorithms that are suitable for discrete-time systems, the proposed algorithm can dynamically adjust the update speed of the ESN's state and, hence, it can enable the UAVs to learn the continuous dynamics of their associated VR users. Simulation results show that the proposed algorithm achieves up to 14% and 27.1% gains in terms of total VR QoE for all users compared to Q-learning using LTE-U and Q-learning using LTE

    A Multi-Game Framework for Harmonized LTE-U and WiFi Coexistence over Unlicensed Bands

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    The introduction of LTE over unlicensed bands (LTE-U) will enable LTE base stations (BSs) to boost their capacity and offload their traffic by exploiting the underused unlicensed bands. However, to reap the benefits of LTE-U, it is necessary to address various new challenges associated with LTE-U and WiFi coexistence. In particular, new resource management techniques must be developed to optimize the usage of the network resources while handling the interdependence between WiFi and LTE users and ensuring that WiFi users are not jeopardized. To this end, in this paper, a new game theoretic tool, dubbed as \emph{multi-game} framework is proposed as a promising approach for modeling resource allocation problems in LTE-U. In such a framework, multiple, co-existing and coupled games across heterogeneous channels can be formulated to capture the specific characteristics of LTE-U. Such games can be of different properties and types but their outcomes are largely interdependent. After introducing the basics of the multi-game framework, two classes of algorithms are outlined to achieve the new solution concepts of multi-games. Simulation results are then conducted to show how such a multi-game can effectively capture the specific properties of LTE-U and make of it a "friendly" neighbor to WiFi.Comment: Accepted for publication at IEEE Wireless Communications Magazine, Special Issue on LTE in Unlicensed Spectru

    Ruin Theory for Dynamic Spectrum Allocation in LTE-U Networks

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    LTE in the unlicensed band (LTE-U) is a promising solution to overcome the scarcity of the wireless spectrum. However, to reap the benefits of LTE-U, it is essential to maintain its effective coexistence with WiFi systems. Such a coexistence, hence, constitutes a major challenge for LTE-U deployment. In this paper, the problem of unlicensed spectrum sharing among WiFi and LTE-U system is studied. In particular, a fair time sharing model based on \emph{ruin theory} is proposed to share redundant spectral resources from the unlicensed band with LTE-U without jeopardizing the performance of the WiFi system. Fairness among both WiFi and LTE-U is maintained by applying the concept of the probability of ruin. In particular, the probability of ruin is used to perform efficient duty-cycle allocation in LTE-U, so as to provide fairness to the WiFi system and maintain certain WiFi performance. Simulation results show that the proposed ruin-based algorithm provides better fairness to the WiFi system as compared to equal duty-cycle sharing among WiFi and LTE-U.Comment: Accepted in IEEE Communications Letters (09-Dec 2018

    Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

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    Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

    Energy Efficiency and Throughput Optimization in 5G Heterogeneous Networks

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    Device to device communication offers an optimistic technology for 5G network which aims to enhance data rate, reduce latency and cost, improve energy efficiency as well as provide other desired features. 5G heterogeneous network (5GHN) with a decoupled association strategy of downlink (DL) and uplink (UL) is an optimistic solution for challenges which are faced in 4G heterogeneous network (4GHN). Research work presented in this paper evaluates performance of 4GHN along with DL and UL coupled (DU-CP) access scheme in comparison with 5GHN with UL and DL decoupled (DU-DCP) access scheme in terms of energy efficiency and network throughput in 4-tier heterogeneous networks. Energy and throughput are optimized for both scenarios i.e. DU-CP and DU-DCP and the results are compared. Detailed performance analysis of DU-CP and DU-DCP access schemes has been done with the help of comparisons of results achieved by implementing genetic algorithm (GA) and particle swarm optimization (PSO). Both these algorithms are suited for the non linear problem under investigation where the search space is large. Simulation results have shown that the DU-DCP access scheme gives better performance as compared to DU-CP scheme in a 4-tier heterogeneous network in terms of network throughput and energy efficiency. PSO achieves an energy efficiency of 12 Mbits/joule for DU-CP and 42 Mbits/joule for DU-DCP, whereas GA yields an energy efficiency of 28 Mbits/joule for DU-CP and 55 Mbits/joule for DU-DCP. Performance of the proposed method is compared with that of three other schemes. The results show that the DU-DCP scheme using GA outperforms the compared methods

    On three use cases of multi-connectivity paradigm in emerging wireless networks

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    As envisioned by global network operators, the increasing trend of data traffic demand is expected to continue with exponential growth in the coming years. To cope with this rapid increase, significant efforts from the research community, industry and even regulators have been focused towards improving two main aspects of the wireless spectrum: (i) spectrum capacity and (ii) spectral efficiency. Concerning the spectrum capacity enhancement, the multi-connectivity paradigm has been seen to be fundamentally important to solve the capacity problem in the next generation networks. Multi-connectivity is a feature that allows wireless devices to establish and maintain multiple simultaneous connections across homogeneous or heterogeneous technologies. In this thesis, we focus on identifying the core issues in applying the multi-connectivity paradigm for different use cases and propose novel solutions to address them. Specifically, this thesis studies three use cases of the multi-connectivity paradigm. First, we study the uplink/downlink decoupling problem in 4G networks. More specifically, we focus on the user association problem in the decoupling context, which is considered challenging due to the conflicting objectives of different entities (e.g., mobile users and base stations) in the system. We use a combination of matching theory and stochastic geometry to reconcile competing objectives between users in the uplink/downlink directions and also from the perspective of base stations. Second, we tackle the spectrum aggregation problem for wireless backhauling links in unlicensed opportunistic shared spectrum bands, specifically, TV White Space (TVWS) spectrum. In relation to this, we present a DIY mobile network deployment model to accelerate the roll-out of high-end mobile services in rural and developing regions. As part of this model, we highlight the importance of low-cost and high-capacity backhaul infrastructure for which TVWS spectrum can be exploited. Building on that, we conduct a thorough analytical study to identify the characteristics of TVWS in rural areas. Our study sheds light on the nature of TVWS spectrum fragmentation for the backhauling use case, which in turn poses requirements for the design of spectrum aggregation systems for TVWS backhaul. Motivated by these findings, we design and implement WhiteHaul, a flexible platform for spectrum aggregation in TVWS. Three challenges have been tackled in this work. First, TVWS spectrum is fragmented in that the spectrum is available in non-contiguous manner. To fully utilize the available spectrum, multiple radios should be enabled to work simultaneously. However, all the radios have to share only a single antenna. The key challenge is to design a system architecture that is capable of achieving different aggregation configurations while avoiding the interference. Second, the heterogeneous nature of the available spectrum (i.e., in terms of bandwidth and link characteristics) requires a design of efficient traffic distribution algorithm that takes into account these factors. Third, TVWS is unlicensed opportunistic shared spectrum. Thus, the coordination mechanism between the two nodes of backhauling link is essential to enable seamless channel switching. Third, we study the integration of multiple radio access technologies (RATs) in the context of 4G/5G networks. More specifically, we study the potential gain of enabling the Multi-RAT integration at the Packet Data Convergence Protocol (PDCP) layer compared with doing it at the transport layer. In this work, we consider ultra-reliable low-latency communication (URLLC) as one of the motivating services. This work tackles the different challenges that arise from enabling the Multi-RAT integration at the PDCP layer, including, packet reordering and traffic scheduling
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