Rendezvous is a fundamental building block in distributed cognitive-radio networks (CRNs), in which pairs or groups of users must find a jointly available channel. Research on the rendezvous problem has focused so far on minimizing the time to rendezvous (to find a suitable channel) or on maximizing the rendezvous degree (percentage of channels on which rendezvous can take place). In this paper, we model the rendezvous problem in a more realistic way that acknowledges the fact that available channels may suffer from interference which varies from location to location as well as over time. In other words, channels are influenced by heterogeneous interference. In this setting, CRNs benefit from rendezvous methods that find a quiet channel, which supports high symbol rates and does not suffer much from dropped packets. In this paper, we propose three important rendezvous design disciplines to achieve bounded rendezvous time, full rendezvous degree, and to rendezvous on quiet channels that suffer little interference. We first present the Disjoint Relaxed Difference Set (DRDS) based rendezvous algorithm as a cornerstone, which ensures rendezvous on every channel (full rendezvous degree) in bounded time. When channels suffer from heterogeneous interference, we propose the Interference based DRDS (I-DRDS) algorithm which ensures rendezvous on channels with less interference, incorporating the interference normalization and interference mapping methods. We conduct extensive simulations to evaluate the proposed algorithms; compared with the state-of-the-art algorithms, the results show that I-DRDS has the best rendezvous performance on less interfered channels, with slightly larger rendezvous time.

中文翻译：

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认知无线电网络中异构干扰的有效交会

Rendezvous 是分布式认知无线电网络 (CRN) 中的基本构建块，其中成对或组用户必须找到共同可用的频道。迄今为止，对会合问题的研究主要集中在最小化会合时间（以找到合适的频道）或最大化会合度（可以发生会合的频道的百分比）。在本文中，我们以更现实的方式对会合问题进行建模，该方式承认可用信道可能会受到不同位置以及随时间变化的干扰的影响。换句话说，信道受到异构干扰的影响。在这种情况下，CRN 受益于找到安静信道的集合点方法，该信道支持高符号率并且不会受到丢包的影响。在本文中，我们提出了三个重要的会合设计原则，以实现有界会合时间、完全会合度以及在几乎不受干扰的安静信道上会合。我们首先提出基于不相交松弛差分集（DRDS）的交会算法作为基石，它确保在有限时间内在每个通道（完全交会度）上交会。当信道受到异构干扰时，我们提出了基于干扰的 DRDS (I-DRDS) 算法，该算法结合了干扰归一化和干扰映射方法，确保在干扰较少的信道上会合。我们进行了广泛的模拟来评估所提出的算法；与最先进的算法相比，结果表明 I-DRDS 在较少干扰的信道上具有最佳的交会性能，