To improve end-to-end throughput and to reduce signaling overhead in multi-hop relay networks, broadcast virtual multiple-input and multiple-output (MIMO) systems (BVMSs) have been introduced. Conventionally, this res...
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To improve end-to-end throughput and to reduce signaling overhead in multi-hop relay networks, broadcast virtual multiple-input and multiple-output (MIMO) systems (BVMSs) have been introduced. Conventionally, this research has been done for a limited environment where each node is equipped with a single-antenna and also interference from other networks is not included for the numerical analysis. In this paper, we propose a new virtual MIMO broadcasting transceiver (VMBT) to overcome the limitation of conventional BVMS and to improve end-to-end throughput for BVMS-based multi-hop-relay networks while the signaling overhead effectively reduced. Toward this goal, proposed VMBT is designed based on the following contributions: analysis of the channel ellipse property, convergence proof of the iterative algorithm and utilization of the null and span of channel vectors. The simulation results show that the proposed VMBT achieves the highest end-to-end throughput compared with that of other conventional technologies. (C) 2015 Elsevier Inc. All rights reserved.
The main purpose of this paper is to construct a new iterative algorithm using the notion of P-eta-resolvent operator for solving a new system of generalized multi-valued variational-like inclusions in the setting of ...
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The main purpose of this paper is to construct a new iterative algorithm using the notion of P-eta-resolvent operator for solving a new system of generalized multi-valued variational-like inclusions in the setting of Banach spaces. As an application of the constructed algorithm, the strong convergence of the sequences generated by our proposed iterative algorithm to a solution of the system of generalized multi-valued variational-like inclusions is proved.
This paper treats the multidimensional application of a previous iterative Monte Carlo algorithm that enables the computation of approximations in L(2). The case of regular functions is studied using a Fourier basis o...
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This paper treats the multidimensional application of a previous iterative Monte Carlo algorithm that enables the computation of approximations in L(2). The case of regular functions is studied using a Fourier basis on periodised functions, Legendre and Tchebychef polynomial bases. The dimensional effect is reduced by computing these approximations on Korobov-like spaces. Numerical results show the efficiency of the algorithm for both approximation and numerical integration. (C) 2003 Elsevier B.V. All rights reserved.
This work presents an efficient monotonic algorithm for the numerical solution of the obstacle problem and the Signorini problems, when they are discretized either by the finite element method or by the finite volume ...
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This work presents an efficient monotonic algorithm for the numerical solution of the obstacle problem and the Signorini problems, when they are discretized either by the finite element method or by the finite volume method. The convergence of this algorithm applied to the discrete problem is proven in both cases.
In this paper, we introduce a general iterative algorithm for finding a common element of the set of common fixed points of an infinite family of nonexpansive mappings and the set of solutions of systems of variationa...
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In this paper, we introduce a general iterative algorithm for finding a common element of the set of common fixed points of an infinite family of nonexpansive mappings and the set of solutions of systems of variational inequalities for two inverse strongly accretive mappings in a q-uniformly smooth Banach space. Then, we prove a strong convergence theorem for the iterative sequence generated by the proposed iterative algorithm under very mild conditions. The methods in the paper are novel and different from those in the early and recent literature. Our results can be viewed as improvement, supplementation, development and extension of the corresponding results in some references to a great extent.
How to improve the coverage capability of network including connectivity and throughput is vital for enabling the Internet of Everything (IoE) in B5G/6G. However, the traditional terrestrial networks are confronted wi...
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How to improve the coverage capability of network including connectivity and throughput is vital for enabling the Internet of Everything (IoE) in B5G/6G. However, the traditional terrestrial networks are confronted with the high-cost and inflexible challenges especially in the remote area and emergency applications. In order to solve these challenges, we consider a heterogeneous aerial network (HetAN), where some low-altitude base stations (LBSs) are deployed as access points for wireless coverage and a high-altitude base station (HBS) hovers as the hub for backhaul of LBSs. Furthermore, we apply the non-orthogonal multiple access (NOMA) to uplink transmission for the terrestrial users, which enable massive connectivity in the IoE. To maximize connectivity and throughput, we jointly optimize the LBSs' deployment, power control, channel allocation, and rate control by fully exploiting the potential of the HetAN in wide-area coverage. For solving the formulated problem efficiently, we propose an iterative algorithm based on the methods of graph theory, bionic algorithm, and theoretical analysis. Simulation results are provided to reveal the influence of the control variables on network performance and indicate that our algorithm can greatly improve the connectivity and throughput with the other schemes.
In this work, we consider the problem of consensus of multiple attribute group decision making, and develop an automatic approach to reaching consensus among group opinions. In the process of group decision making, ea...
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In this work, we consider the problem of consensus of multiple attribute group decision making, and develop an automatic approach to reaching consensus among group opinions. In the process of group decision making, each expert provides his/her preferences over the alternatives with respect to each attribute, and constructs an individual decision matrix. The developed approach first aggregates these individual decision matrices into a group decision matrix by using the additive weighted aggregation (AWA) operator, and then establishes a convergent iterative algorithm to gain a consentaneous group decision matrix. Then based on the consentaneous group decision matrix, the approach utilizes the AWA operator to derive the overall attribute values of alternatives, by which the most desirable alternative can be found out. Finally, we detailedly expound the implementation process of the approach with a practical example. (C) 2008 Elsevier Ltd. All rights reserved.
Let K be a closed convex subset of a Banach space X. We consider complete metric spaces of self-mappings of K which are nonexpansive with respect to a convex function on X. We prove that the iterates of a generic oper...
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Let K be a closed convex subset of a Banach space X. We consider complete metric spaces of self-mappings of K which are nonexpansive with respect to a convex function on X. We prove that the iterates of a generic operator in these spaces converge strongly. In some cases the limits do not depend on the initial points and are the unique fixed point of the operator.
This paper studies the two-impulse cotangent rendezvous problem between two coplanar elliptical orbits. This problem requires the same flight time for two spacecraft and a cotangent transfer between the initial and fi...
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This paper studies the two-impulse cotangent rendezvous problem between two coplanar elliptical orbits. This problem requires the same flight time for two spacecraft and a cotangent transfer between the initial and final orbits. For two coplanar circular orbits, the closed-form solution is obtained and its total cost is equal to that of the Hohmann transfer. However, for two coplanar elliptical orbits, the solutions are obtained only by a numerical iterative algorithm. There are many solutions for the multiple-revolution case. Moreover, the minimum-fuel two-impulse cotangent transfer can be expressed as the true anomaly of final orbit. With the minimum-fuel transfer, a simple method for the optimal revolution numbers is proposed based on the first-order Taylor series expansion of the flight-time equation. Then, the minimum-fuel two-impulse cotangent rendezvous is obtained by calculating and comparing two or four candidates. Two numerical examples are provided to apply the proposed technique for all solutions and the minimum-fuel solution to the two-impulse cotangent rendezvous problem.
In this paper, we propose a class of stable finite difference schemes for the initial-boundary value problem of the Cahn-Hilliard equation. These schemes are proved to inherit the total mass conservation and energy di...
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In this paper, we propose a class of stable finite difference schemes for the initial-boundary value problem of the Cahn-Hilliard equation. These schemes are proved to inherit the total mass conservation and energy dissipation in the discrete level. The dissipation of the total energy implies boundness of the numerical solutions in the discrete H1 norm. This in turn implies boundedness of the numerical solutions in the maximum norm and hence the stability of the difference schemes. Unique existence of the numerical solutions is proved by the fixed-point theorem. Convergence rate of the class of finite difference schemes is proved to be O（h2 ＋ r2） with time step T and mesh size h. An efficient iterative algorithm for solving these nonlinear schemes is proposed and discussed in detail.
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