1,113 research outputs found

    Tutorial on LTE/LTE-A Cellular Network Dimensioning Using Iterative Statistical Analysis

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    LTE is the fastest growing cellular technology and is expected to increase its footprint in the coming years, as well as progress toward LTE-A. The race among operators to deliver the expected quality of experience to their users is tight and demands sophisticated skills in network planning. Radio network dimensioning (RND) is an essential step in the process of network planning and has been used as a fast, but indicative, approximation of radio site count. RND is a prerequisite to the lengthy process of thorough planning. Moreover, results from RND are used by players in the industry to estimate preplanning costs of deploying and running a network; thus, RND is, as well, a key tool in cellular business modelling. In this work, we present a tutorial on radio network dimensioning, focused on LTE/LTE-A, using an iterative approach to find a balanced design that mediates among the three design requirements: coverage, capacity, and quality. This approach uses a statistical link budget analysis methodology, which jointly accounts for small and large scale fading in the channel, as well as loading due to traffic demand, in the interference calculation. A complete RND manual is thus presented, which is of key importance to operators deploying or upgrading LTE/LTE-A networks for two reasons. It is purely analytical, hence it enables fast results, a prime factor in the race undertaken. Moreover, it captures essential variables affecting network dimensions and manages conflicting targets to ensure user quality of experience, another major criterion in the competition. The described approach is compared to the traditional RND using a commercial LTE network planning tool. The outcome further dismisses the traditional RND for LTE due to unjustified increase in number of radio sites and related cost, and motivates further research in developing more effective and novel RND procedures

    Reinforcement Learning-Based Load Balancing Satellite Handover Using NS-3

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    The Fifth-Generation of Mobile Communications (5G) is intended to meet users' growing needs for high-quality services at any time and from any location. The unique features of Low Earth Orbit (LEO) satellites in terms of higher coverage, reliability, and availability, can help expand the reach of 5G and beyond technologies to support those needs. However, because of their high speeds, a single LEO satellite is unable to provide continuous service to multiple User Equipments (UEs) spread over a large (potentially worldwide) area, resulting in the need for LEO satellite constellations with a high number of satellites and a consequent high amount of satellite handovers (HOs). Moreover, UEs can only acquire partial information about the satellite system and compete for the limited available communication resources of the satellites, requiring the implementation of a decentralized satellite HO strategy to avoid network congestion. In this paper, we propose a decentralized Load Balancing Satellite HO (LBSH) strategy based on multi-agent reinforcement Q-learning, implemented within the software Network Simulator 3 (NS-3). LBSH aims to reduce the total number of HOs and the blocking rate while balancing the load distribution among satellites. Our results show that the proposed LBSH method outperforms the state-of-the-art methods in terms of a 95% drop in the average number of HOs per user and an 84% reduction in blocking rate

    Multi-input multi-output (MIMO) detection by a colony of ants

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    The traditional mobile radio channel has always suffered from the detrimental effects of multipath fading. The use of multiple antennae at both ends of the wireless channel has proven to be very effective in combatting fading and enhancing the channel's spectral efficiency. To exploit the benefits offered by Multi-Input Multi-Output (MIMO) systems, both the transmitter and the receiver have to be optimally designed. In this thesis, we are concerned with the problem of receiver design for MIMO systems in a spatial multiplexing scheme. The MIMO detection problem is an NP-hard combinatorial optimization problem. Solving this problem to optimality requires an exponential search over the space of all possible transmitted symbols in order to find the closest point in a Euclidean sense to the received symbols; a procedure that is infeasible for large systems. We introduce a new heuristic algorithm for the detection of a MIMO wireless system based on the Ant Colony Optimization (ACO) metaheuristic. The new algorithm, AntMIMO, has a simple architecture and achieves near maximum likelihood performance in polynomial time

    Quantum three-body system in D dimensions

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    The independent eigenstates of the total orbital angular momentum operators for a three-body system in an arbitrary D-dimensional space are presented by the method of group theory. The Schr\"{o}dinger equation is reduced to the generalized radial equations satisfied by the generalized radial functions with a given total orbital angular momentum denoted by a Young diagram [μ,ν,0,...,0][\mu,\nu,0,...,0] for the SO(D) group. Only three internal variables are involved in the functions and equations. The number of both the functions and the equations for the given angular momentum is finite and equal to (μν+1)(\mu-\nu+1).Comment: 16 pages, no figure, RevTex, Accepted by J. Math. Phy
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