Power consumption is a major limitation in the downlink of multibeam
satellite systems, since it has a significant impact on the mass and lifetime
of the satellite. In this context, we study a new energy-aware power allocation
problem that aims to jointly minimize the unmet system capacity (USC) and total
radiated power by means of multi-objective optimization. First, we transform
the original nonconvex-nondifferentiable problem into an equivalent
nonconvex-differentiable form by introducing auxiliary variables. Subsequently,
we design a successive convex approximation (SCA) algorithm in order to attain
a stationary point with reasonable complexity. Due to its fast convergence,
this algorithm is suitable for dynamic resource allocation in emerging on-board
processing technologies. In addition, we formally prove a new result about the
complexity of the SCA method, in the general case, that complements the
existing literature where the complexity of this method is only numerically
analyzed.

本文研究了一种新的能量感知的功率分配问题，旨在通过多目标优化共同最小化未满足的系统容量（USC）和总辐射功率。为了实现合理的复杂度，我们设计了连续凸逼近（SCA）算法，使原问题转化为等效的非凸可微问题。此算法适合于新兴的机载处理技术中的动态资源分配。同时，我们还正式证明了有关 SCA 算法复杂度的新结果，补充了现有文献中对该算法复杂度的只数值分析的情况。

多波束卫星系统中动态能效功率分配

Dynamic Energy-Efficient Power Allocation in Multibeam Satellite Systems

Merging mobile edge computing (MEC) functionality with the dense deployment
of base stations (BSs) provides enormous benefits such as a real proximity, low
latency access to computing resources. However, the envisioned integration
creates many new challenges, among which mobility management (MM) is a critical
one. Simply applying existing radio access oriented MM schemes leads to poor
performance mainly due to the co-provisioning of radio access and computing
services of the MEC-enabled BSs. In this paper, we develop a novel user-centric
energy-aware mobility management (EMM) scheme, in order to optimize the delay
due to both radio access and computation, under the long-term energy
consumption constraint of the user. Based on Lyapunov optimization and
multi-armed bandit theories, EMM works in an online fashion without future
system state information, and effectively handles the imperfect system state
information. Theoretical analysis explicitly takes radio handover and
computation migration cost into consideration and proves a bounded deviation on
both the delay performance and energy consumption compared to the oracle
solution with exact and complete future system information. The proposed
algorithm also effectively handles the scenario in which candidate BSs randomly
switch on/off during the offloading process of a task. Simulations show that
the proposed algorithms can achieve close-to-optimal delay performance while
satisfying the user energy consumption constraint.

本文提出了一种基于 Lyapunov 优化和多臂赌博理论的用户为中心、能源感知的移动性管理 (EMM) 方案，以优化因无线电接入和计算引起的延迟，并保证用户能源消耗的长期限制。此方案通过在线方式工作，可以有效处理不完整的系统状态信息和随机开关候选基站的情况，实现接近最优的时延性能和满足用户能源消耗的约束条件。