As per the most recent literature, Orthogonal Frequency Division Multiplexing (OFDM), a multi access technique, is considered most suitable for the 3G, 4G and 5G techniques in high speed wireless communication. What made OFDM most popular is its ability to deliver high bandwidth efficiency and superior data rate. Besides it, high value of peak to average power ratio (PAPR) and Inter Carrier Interference (ICI) are the challenges to tackle down via appropriate mitigation scheme. As a research contribution in the present work, an improved self-cancellation (SC) technique is designed and simulated through Simulink to mitigate the effect of ICI. This novel proposed technique (Improved SC) is designed over discrete wavelet transform (DWT) based OFDM and compared with conventional SC scheme over different channel conditions i.e. AWGN and Rayleigh fading environments. It is found that proposed DWT-OFDM with Improved SC scheme outperforms conventional SC technique significantly, under both AWGN and Rayleigh channel conditions. Further, in order to justify the novelty in the research contribution, a Split-DWT based Simulink model for Improved SC scheme is investigated to analyse the BER performance. This Split-DWT based Simulink model presented here foretells the future research potential in wavelet hybridization of OFDM to side-line ICI effects more efficiently.
相似用户挖掘是提高社交网络服务质量的重要途径,在面向大数据的社交网络时代,准确的相似用户挖掘对于用户和互联网企业等都有重要的意义,而根据用户自己的兴趣话题挖掘的相似用户更符合相似用户的要求。提出了一种基于用户兴趣话题进行相似用户挖掘的方法。该方法首先使用TextRank话题提取方法对用户进行兴趣话题提取,再对用户发表内容进行训练,计算出所有词之间的相似度。提出CP(Corresponding Position similarity)、CPW(Corresponding Position Weighted similarity)、AP(All Position similarity)、APW(All Position Weighted similarity)四种用户兴趣话题词相似度计算方法,通过用户和相似用户间关注、粉丝重合率验证相似用户挖掘效果,APW similarity的相似用户的关注/粉丝重合百分比为1.687%,优于提出的其他三种算法,分别提高了26.3%、2.8%、12.4%,并且比传统的文本相似度方法Jaccard相似度、编辑距离算法、余弦相似度分别提高了20.4%、21.2%、45.0%。因此APW方法可以更加有效地挖掘出用户的相似用户。 相似文献