首页> 外文期刊>IEEE Journal on Selected Areas in Communications >Joint Optimization of BS Operation, User Association, Subcarrier Assignment, and Power Allocation for Energy-Efficient HetNets
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Joint Optimization of BS Operation, User Association, Subcarrier Assignment, and Power Allocation for Energy-Efficient HetNets

机译:节能高效的HetNet的BS操作,用户关联,子载波分配和功率分配的联合优化

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Network control strategies for energy-efficient operation of HetNets need to match the dynamics of spatial and temporal traffic loads and to stabilize the network. In this paper, we develop a stochastic optimization framework, which formulates spatially inhomogeneous traffic distributions and time-varyingly random traffic arrivals and guarantees network stability, to investigate the energy conservation problem in HetNets. In particular, we jointly optimize base station (BS) operation, user association, subcarrier assignment, and power allocation to minimize the average energy consumption. We devise an algorithm without requiring any prior-knowledge of traffic distributions, referred to as the Steerable Energy ExpenDiture algorithm (SEED), to solve the problem. To deal with a highly coupled and mixed combinational subproblem in the SEED, we separate optimization variables for suboptimal but cost-efficient and easy-to-implement algorithm design. By this, we develop closed-form solutions for both user association and subcarrier assignment, a fast and tuning-free algorithm that provably achieves at least local optimality for power allocation, and a greedy-style heuristic algorithm for BS operation with polynomial complexity. Simulation results exhibit that the SEED usually converges fast, can flexibly tune the power-delay tradeoff, and can significantly reduce energy consumption against other existing schemes.
机译:为了使HetNet高效运行,网络控制策略需要匹配时空流量负载的动态变化并稳定网络。在本文中,我们开发了一个随机优化框架,该框架可以计算空间上不均匀的流量分布和时变的随机流量到达并保证网络的稳定性,以研究HetNets中的节能问题。特别是,我们共同优化了基站(BS)的运行,用户关联,子载波分配和功率分配,以最大程度地降低平均能耗。我们设计了一种无需任何先验流量分布知识就可以解决此问题的算法,称为可控能源支出算法(SEED)。为了处理SEED中高度耦合和混合的组合子问题,我们将优化变量分开,以实现次优但经济高效且易于实现的算法设计。通过这种方式,我们为用户关联和子载波分配开发了封闭形式的解决方案,一种快速且无需调整的算法(可证明至少实现了功率分配的局部最优)以及一种针对多项式复杂度的BS操作的贪婪风格启发式算法。仿真结果表明,SEED通常收敛迅速,可以灵活地调整功耗延迟权衡,并且与其他现有方案相比,可以显着降低能耗。

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