{"title":"重叠认知网络的性能分析与功率分配策略","authors":"Chih-Hao Lin, F. Tseng, Chao-Yuan Hsu","doi":"10.1109/APSIPA.2014.7041524","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a power allocation strategy for overlay cognitive networks, where each node is equipped with single antenna. Owing to the overly strategy, the secondary user (SU) can help transmitting the primary user's (PU) data and meanwhile can convey itself own data with the superposition coding (SC). We first analyze the bit-error-rate (BER) of the PU and the SU Then, the power allocation strategy is devised by minimizing total power, providing that the BER of the PU and that of SU are guaranteed. Since the BER formulations are not convex, the optimization is difficult to conduct. We then propose two new tractable BER approximations for the PU and SU, which can sophisticatedly transfer the design into a convex problem. The solution can thus be obtained. Simulations verify that our power allocation design is validated for different channel environments.","PeriodicalId":231382,"journal":{"name":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Performance analysis and power allocation strategy in overlay cognitive networks\",\"authors\":\"Chih-Hao Lin, F. Tseng, Chao-Yuan Hsu\",\"doi\":\"10.1109/APSIPA.2014.7041524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a power allocation strategy for overlay cognitive networks, where each node is equipped with single antenna. Owing to the overly strategy, the secondary user (SU) can help transmitting the primary user's (PU) data and meanwhile can convey itself own data with the superposition coding (SC). We first analyze the bit-error-rate (BER) of the PU and the SU Then, the power allocation strategy is devised by minimizing total power, providing that the BER of the PU and that of SU are guaranteed. Since the BER formulations are not convex, the optimization is difficult to conduct. We then propose two new tractable BER approximations for the PU and SU, which can sophisticatedly transfer the design into a convex problem. The solution can thus be obtained. Simulations verify that our power allocation design is validated for different channel environments.\",\"PeriodicalId\":231382,\"journal\":{\"name\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIPA.2014.7041524\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2014.7041524","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Performance analysis and power allocation strategy in overlay cognitive networks
In this paper, we propose a power allocation strategy for overlay cognitive networks, where each node is equipped with single antenna. Owing to the overly strategy, the secondary user (SU) can help transmitting the primary user's (PU) data and meanwhile can convey itself own data with the superposition coding (SC). We first analyze the bit-error-rate (BER) of the PU and the SU Then, the power allocation strategy is devised by minimizing total power, providing that the BER of the PU and that of SU are guaranteed. Since the BER formulations are not convex, the optimization is difficult to conduct. We then propose two new tractable BER approximations for the PU and SU, which can sophisticatedly transfer the design into a convex problem. The solution can thus be obtained. Simulations verify that our power allocation design is validated for different channel environments.