认知无线电在处理频谱稀缺的问题上是一个非常有前途的解决方案。拥有多天线认知无线电的用戶通过发射波束成形技术可以和授权用在同一时刻同一频带共存，这样大大地增强了频谱效率。在实际系统中，最理想的情况是这些拥有多天线认知无线电用戶能够分布式地优化他们的发射波束形成向量以此达到系统的最优化。由于授权用戶受到的干扰是来自于所有认知无线电用戶的，为了实现分布式算法这些干扰必须被合理地规划以至于达到最优。也就是说，每个认知无线电用戶需要知道对授权用戶产生干扰的最佳约束上限。 / 从优化的角度处理这种解耦问题，最常用的方法是原始分解法和对偶分解法。然而这两种方法都需要用戶之间有大量的消息传递，这对于频谱效率来说是有害的。在对偶分解法中，指向授权用戶的耦合干扰被一协调者估测(通常是授权用戶本身)。协调者需要在每次迭代中更新和广播参数给认知无线电用戶。对于原始分解法，算法同样需要一协调者进行收集认知无线电用戶的目标函数信息以此计算每个用戶的最优干扰约束上限。协调者同样需要更新和广播大量消息给认知无线电用戶。这种大量的信息计算和传递在分布式系统中是不理想的，问题在认知无线电网络显得格外严重。因为授权用戶不希望担任这样的协调者除非他的计算参与降到最低。 / 在此论文中，我们提出了几种新型的基于认知无线电网络的分布式算法。目的是最小化授权用戶和认知无线电用戶的消息传递。通过研究半定规划中的最优分割法，我们指出不影响最优性条件下授权用戶和认知无线电用戶的大量消息传递是可以避免的。我们又提出了在多输入多数出认知无线电网络中一种基于对偶分解的鲁捧干扰控制。在此论文中提出的低消息传递算法大大地提高了多用戶多输入多数认知无线电网络的实用性。 / Cognitive radio (CR) is a promising solution to alleviate spectrum scarcity. In CR networks where mobile stations are equipped with multiple antennas, secondary users (SUs) can transmit at the same time as the primary users (PUs) by carefully controlling the interference through transmit beamforming, thus significantly enhancing the spectrum efficiency. In practical systems, it is desirable to have multiple SUs optimize their transmit beamforming vectors in a decentralized manner, and yet achieve an optimal system performance. In CR networks, the interference received by the PU is attributed to the transmission of all SUs. To facilitate distributed beamforming, the aggregate-interference constraint imposed by the PU must be decoupled, so that each individual SU knows the "fair share" of interference that is allowed to generate to the PU. / A commonly used technique for decoupling coupled constraintsin optimization problems is optimization decomposition, including dual and primal decompositions. Both the dual and primal decomposition methods require frequent message passing among users, which potentially offsets the spectrum benefit brought by cognitive radio techniques. Specifically, with dual decomposition, the aggregate interference generated to the PU must be measured by a coordinator,which is, naturally, the PU. The coordinator then updates and broadcasts the Lagrangian multiplier to all SUs. Likewise, the primal decomposition needs a coordinator, which can again be the PU, to gather the subgradient of the objective functions of each SUs for given interference partition. The coordinator then updates and broadcasts the permissible interference to all SUs. Whereas the large overhead incurred message computation and passing is undesirable in distributed systems, the problem is more acute in CR networks, because a typical PU would not be willing to take the coordinating role unless its involvement is minimized. / In this thesis, we propose several novel distributed optimization algorithms for CR networks with minimum message passing between the primary and secondary systems. By exploiting the theory of optimal partition (OP) for semi-definite programming (SDP), we show that most message passings between the primary and secondary systems can be eliminated without compromising the optimality of the solution. We also derive a robust interference control scheme based on the duality theory for MIMO CR network. The low message-passing distributed algorithms presented in this thesis greatly enhance the practicality of multiuser MIMO CR networks. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Yao, Leiyi. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 114-123). / Abstracts also in Chinese.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_1077682 |
| Date | January 2014 |
| Contributors | Yao, Leiyi (author.), Zhang, Ying Jun (thesis advisor.), Chinese University of Hong Kong Graduate School. Division of Information Engineering, (degree granting institution.) |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography, text |
| Format | electronic resource, electronic resource, remote, 1 online resource (xxi, 123 leaves) : illustrations (some color), computer, online resource |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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