不完整資訊下動態頻寬交易之最佳定價方法

Abstract

頻寬是很稀少且珍貴的資源。為了增進頻寬使用效率，解決原先使用方法的低效率，感知無線電(cognitive radio)以及動態頻譜分配(dynamic spectrum allocation)的概念被提了出來。在此篇論文，我們考慮一個由單一 mobile network operator (MNO) 以及眾多有著不同類別(type)的 mobile virtual network operators (MVNOs) 組成的無線網路。我們以下提供一個由兩個階段組成的開放式動態頻寬交易模型來讓 MNO 將頻寬販賣給 MVNOs。 這個開放式動態頻寬交易模型的第一個階段的目的是在一連串MNO與MVNOs的互動中，去找到參與的MVNOs的購買意願或者他們的類別，並且計算出要被販賣的頻寬的最佳價目表。計算最佳價目表的同時也會考慮到MVNOs的需求價格函數以及效用函數。最重要的是，最佳價目表必須滿足誘因相符性(incentive compatible, IC) 以及個體理性(individually rational, IR)的限制。前者確保了為某個類別的MVNO設計的數量-價格組能給該MVNO帶來最大的效用；後者確保了為其設計的數量-價格組可以給其非零的效用。我們同時也提供了一個將連續的最佳價目表轉成離散形式，以提供一個比較容易閱讀的格式；此時每個MVNO都會去選擇最靠近其在連續最佳價目表中類別的數量-價格組。在反覆進行的互動收斂且停止之後，如果全部的需求超出了可以提供的頻寬，那麼此模型就會使用背包問題的解法來將頻寬分配給一部分的MVNOs，已使得分配出去的頻寬不會超出可提通頻寬的限制。最後，我們用一個例子來說明這個開放式動態頻寬交易模型是如何運作的。

The wireless spectrum is a limited resource. The concepts of cognitive radio and dynamic spectrum allocation (DSA) have been considered as a possible mechanism to improve the efficiency of bandwidth usage and solve the bandwidth deficiency problem. In this work, we consider a wireless network access environment comprised of a mobile network operator (MNO) and a distribution of different types of mobile virtual network operators (MVNOs). We propose an open dynamic bandwidth trading model that comprises of two phases. The goal of the phase one is to find out the distribution of the buying preferences or types of the participating MVNOs through a sequence of interactive rounds and compute the optimal price schedule for the unused bandwidth for sale. The derivation of the optimal price schedule also considers the demand and utility functions of the MVNOs. Most importantly, the optimal price schedule satisfies the incentive compatible (IC) and the individually rational (IR) constraints. The former ensures that the quantity-price pair designed for MVNO of a specific type will choose the pair that maximizes its utility; while the latter assures that the pairs cause non-negative utility. We also give an algorithm to convert the continuous optimal price schedule to a discrete one so as to provide a simple easy-to-read format for MVNOs’ selection while ensuring that individual type of MVNOs will choose the pair whose corresponding utility value is closest to the value in the original function. After the iterative process converges and terminates, if the total number of bandwidth requests exceeds the total capacity constraint, the process proceeds to address the finite capacity constraint by solving a bounded knapsack problem for final bandwidth allocation. Lastly, an example is provided to explain how the proposed open dynamic bandwidth trading process with optimal incentive-compatible price schedule is derived.