[论文解读] Joint Power Control and Fronthaul Rate Allocation for Throughput Maximization in OFDMA-based Cloud Radio Access Network

Liang Liu, Suzhi Bi+1 more|arXiv (Cornell University)|Jul 15, 2014

Advanced MIMO Systems Optimization参考文献 13被引用 7

一句话总结

该论文提出了一种基于OFDMA的云无线电接入网络（C-RAN）的联合功率控制与前回程速率分配方案，旨在前回程容量受限条件下最大化系统吞吐量。通过采用实际的均匀标量量化，并联合优化功率与量化，该方案实现了接近容量的性能，相较于单独优化具有显著增益，且在前回程容量足够大时，性能与理论上限重叠。

ABSTRACT

The performance of cloud radio access network (C-RAN) is constrained by the limited fronthaul link capacity under future heavy data traffic. To tackle this problem, extensive efforts have been devoted to design efficient signal quantization/compression techniques in the fronthaul to maximize the network throughput. However, most of the previous results are based on information-theoretical quantization methods, which are hard to implement due to the extremely high complexity. In this paper, we consider using practical uniform scalar quantization in the uplink communication of an orthogonal frequency division multiple access (OFDMA) based C-RAN system, where the mobile users are assigned with orthogonal sub-carriers for multiple access. In particular, we consider joint wireless power control and fronthaul quantization design over the sub-carriers to maximize the system end-to-end throughput. Efficient algorithms are proposed to solve the joint optimization problem when either information-theoretical or practical fronthaul quantization method is applied. Interestingly, we find that the fronthaul capacity constraints have significant impact to the optimal wireless power control policy. As a result, the joint optimization shows significant performance gain compared with either optimizing wireless power control or fronthaul quantization alone. Besides, we also show that the proposed simple uniform quantization scheme performs very close to the throughput performance upper bound, and in fact overlaps with the upper bound when the fronthaul capacity is sufficiently large. Overall, our results would help reveal practically achievable throughput performance of C-RAN, and lead to more efficient deployment of C-RAN in the next-generation wireless communication systems.

研究动机与目标

• 解决在高数据流量场景下，由于前回程容量受限导致的C-RAN吞吐量下降问题。
• 通过在上行链路中采用实际的均匀标量量化，克服信息论量化方法的不切实际复杂度。
• 通过联合优化正交子载波上的无线功率控制与前回程速率分配，最大化系统总吞吐量。
• 证明联合优化显著优于单独优化功率控制或前回程资源分配的性能。
• 在不同前回程约束条件下，评估实际量化与理论吞吐量上限之间的性能差距。

提出的方法

• 针对具有子载波分配、功率控制与前回程量化速率分配的上行链路OFDMA-C-RAN，建立联合优化问题。
• 通过使用均匀标量量化建模前回程为“量化并转发”链路，以降低实现复杂度。
• 提出高效算法，求解在信息论量化与实际量化模型下的非凸优化问题。
• 推导在前回程容量约束下的最优功率分配策略，表明前回程容量直接决定最优功率分布。
• 通过切集界分析建立理论吞吐量上限，并与所提方案性能进行比较。
• 应用凹松弛与基于对偶的优化技术，高效求解联合功率与量化设计问题。

实验结果

研究问题

• RQ1 与单独优化相比，联合优化功率控制与前回程速率分配在OFDMA-C-RAN中如何提升系统吞吐量？
• RQ2 在前回程受限的C-RAN中，实际均匀标量量化在多大程度上逼近信息论量化方法的性能？
• RQ3 前回程容量约束对C-RAN中最佳无线功率控制策略有何影响？
• RQ4 所提实际方案与理论吞吐量上限相比，性能接近程度如何？
• RQ5 在何种前回程容量条件下，实际方案性能可与理论上限无法区分？

主要发现

• 联合优化功率控制与前回程速率分配相较于单独优化任一组件，均能实现显著的吞吐量增益。
• 所提出的实际均匀标量量化方案性能极为接近理论吞吐量上限，当前回程容量足够大时，性能与上限重叠。
• 前回程容量约束对最优功率控制策略具有决定性影响，凸显联合设计对性能最大化的必要性。
• 当前回程容量较高时，所提方案的系统吞吐量与理论切集界完全匹配，表明其接近最优性能。
• 随着前回程容量增加，所提方案与理论上限之间的性能差距逐渐缩小，验证了方案的可扩展性与高效性。
• 所提方案实现的和速率超过基于切集界的下限，其超出幅度取决于前回程与功率约束，验证了其有效性。