在下一世代的無線通信系統中，以毫米波(mmWave)為基礎的傳輸技術已經被廣泛認為是一項重大的進步，毫米波傳輸可為各種服務提供充足的頻譜資源。除此之外，在基於毫米波的系統中，將設備間直接通訊(D2D)的通信網絡(DN)再加入蜂巢式網路(CN)之中，將會是利用空間資源的重要突破之一。提出一個在DN和CN之間，有效率的頻譜共享策略，可以有效地提高整體頻譜效率(SE)。在本文中，我們研究於DN和CN之間的多對多頻譜共享，具體地來說，蜂巢式網路用戶擁有屬於自己的正交通道，並且再適當地去佈署多個D2D廣播群組來共享蜂巢式網路的通道。同時，我們假定在所有設備上均有搭載均勻線性天線陣列(ULA)，以增強毫米波傳輸的方向性，因此又可以有效地利用空間資源。不僅如此，我們提出透過廣播設備利用旋轉波束方向的方式來執行廣播任務，也進而消除了多對多頻譜共享所引起的強烈干擾。接著，在我們所考慮的系統場景上，我們提出了三種頻譜共享的演算法，包括貪婪演算法，啟發式演算法和自適應性的Gale-Shapley(AGS)方案。通過模擬結果驗證，AGS算法的表現可以明顯地接近整體SE的上限(即貪婪演算法)，同時將AGS的計算複雜度抑制在啟發式演算法的常數倍率之內。

In the future generation of wireless communication systems, the milli-meter wave (mmWave) based transmission technology has been widely recognized as an important revolution to provide sufficient spectrum resources for varieties of services. Moreover, in the mmWave-based system, embedding the device-to-device (D2D) communication network (DN) into the cellular network (CN) is one of the important breakthroughs to utilize the spatial resources. To this end, an efficient spectrum sharing strategy between the DN and CN can effectively boost the overall spectrum efficiency (SE). In this paper, we investigate the many-to-many spectrum sharing between the DN and CN. Specifically, multiple D2D broadcasting groups are properly arranged to share multiple orthogonal channels owned by the cellular users. Also, the uniform linear antenna array (ULA) is deployed at all the devices to strengthen the transmission directionality of mmWave such that the spatial resources can be effectively utilized. And accordingly, the broadcasting task is carried out by rotating the beam direction, which eliminates stronger interference incurred by many-to-many spectrum sharing. Then, on top of the considered system scenario, three spectrum sharing algorithms are proposed, including the Greedy, Heuristic and adaptive Gale-Shapley (AGS) schemes. Verified by the simulation results, the performance of the AGS algorithm can well approach the upper bound (i.e., the Greedy algorithm) in terms of the overall SE, while restraining its computation complexity to just a constant multiple of that for the Heuristic algorithm.

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