Distributed Filter Design and Power Allocation for Small-Cell MIMO Networks

We firstly formulate the energy efficiency (EE) maximization problem of joint user association and power allocation considering minimum data rate requirement of small cell users (SUEs) and maximum transmit power constraint of small cell base stations (SBSs), which is NP-hard. Then, we propose a dynamic coordinated multipoint joint transmission (CoMP-JT) algorithm to improve EE. In the first phase, SUEs are associated with the SBSs close to them to reduce the loss of power by the proposed user association algorithm, where the associated SBSs of each small cell user (SUE) form a dynamic CoMP-JT set. In the second phase, through the methods of fractional programming and successive convex approximation, we transform the EE maximization subproblem of power allocation for SBSs into a convex problem that can be solved by proposed power allocation optimization algorithm. Moreover, we show that the proposed solution has a much lower computational complexity than that of the optimal solution obtained by exhaustive search. Simulation results demonstrate that the proposed solution has a better performance.

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Distributed filter design for cooperative ho-type estimation

2015 IEEE Conference on Control Applications (CCA) ◽

10.1109/cca.2015.7320803 ◽

2015 ◽

Cited By ~ 2

Author(s):

Jingbo Wu ◽

Li Li ◽

Valery Ugrinovskii ◽

Frank Allgower

Keyword(s):

Filter Design ◽

Distributed Filter

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Coexistence of Cognitive Small Cell and WiFi System: A Traffic Balancing Dual-Access Resource Allocation Scheme

Wireless Communications and Mobile Computing ◽

10.1155/2018/4092681 ◽

2018 ◽

Vol 2018 ◽

pp. 1-17 ◽

Cited By ~ 2

Author(s):

Xiaoge Huang ◽

Yangyang Li ◽

She Tang ◽

Qianbin Chen

Keyword(s):

Power Allocation ◽

Optimization Problems ◽

Holistic Approach ◽

Data Rate ◽

Small Cell ◽

Dual Band ◽

Cell Selection ◽

Allocation Scheme ◽

Traffic Balancing ◽

Unlicensed Bands

We consider a holistic approach for dual-access cognitive small cell (DACS) networks, which uses the LTE air interface in both licensed and unlicensed bands. In the licensed band, we consider a sensing-based power allocation scheme to maximize the sum data rate of DACSs by jointly optimizing the cell selection, the sensing operation, and the power allocation under the interference constraint to macrocell users. Due to intercell interference and the integer nature of the cell selection, the resulting optimization problems lead to a nonconvex integer programming. We reformulate the problem to a nonconvex power allocation game and find the relaxed equilibria, quasi-Nash equilibrium. Furthermore, in order to guarantee the fairness of the whole system, we propose a dynamic satisfaction-based dual-band traffic balancing (SDTB) algorithm over licensed and unlicensed bands for DACSs which aims at maximizing the overall satisfaction of the system. We obtain the optimal transmission time in the unlicensed band to ensure the proportional fair coexistence with WiFi while guaranteeing the traffic balancing of DACSs. Simulation results demonstrate that the SDTB algorithm could achieve a considerable performance improvement relative to the schemes in literature, while providing a tradeoff between maximizing the total data rate and achieving better fairness among networks.

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