{"title":"上行认知OFDMA系统中受特定服务质量约束的发射功率优化分配","authors":"L. Akter, N. Nahar","doi":"10.17706/ijcce.2020.9.3.105-121","DOIUrl":null,"url":null,"abstract":"This paper investigates an optimal allocation of transmit power for uplink cognitive OFDMA system. The aim is to construct two optimization frameworks namely, framework-I and II for uplink cognitive OFDMA system that minimizes it’s transmit power while maintaining Quality of Service (QoS). The measures for QoS include SNR threshold for framework-I whereas, for framework-II, it is measured by minimum rate requirement (bits/sec/Hz) to obtain a certain bit error rate (BER). Simulation results reveal the effectiveness of the proposed frameworks. Additionally, for framework-I, effects of different SNR threshold and users’ power budget are observed on the allocation of transmit power. Whereas, for framework-II, effects of different target BER, users’ power budget and minimum rate requirement are observed on the allocation of transmit power. Results are also compared with the results obtained from conventional capacity maximization based resource allocation approaches in terms of allocated transmit power, energy efficiency (EE) and spectral efficiency (SE). Simulation results reveal that, the proposed frameworks are incredibly successful in terms of utilization of power budget of users and EE compared to conventional capacity maximization based resource allocation approaches.","PeriodicalId":23787,"journal":{"name":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","volume":"30 1","pages":"105-121"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Specific Quality of Service Constrained Optimal Allocation of Transmit Power in Uplink Cognitive OFDMA System\",\"authors\":\"L. Akter, N. Nahar\",\"doi\":\"10.17706/ijcce.2020.9.3.105-121\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates an optimal allocation of transmit power for uplink cognitive OFDMA system. The aim is to construct two optimization frameworks namely, framework-I and II for uplink cognitive OFDMA system that minimizes it’s transmit power while maintaining Quality of Service (QoS). The measures for QoS include SNR threshold for framework-I whereas, for framework-II, it is measured by minimum rate requirement (bits/sec/Hz) to obtain a certain bit error rate (BER). Simulation results reveal the effectiveness of the proposed frameworks. Additionally, for framework-I, effects of different SNR threshold and users’ power budget are observed on the allocation of transmit power. Whereas, for framework-II, effects of different target BER, users’ power budget and minimum rate requirement are observed on the allocation of transmit power. Results are also compared with the results obtained from conventional capacity maximization based resource allocation approaches in terms of allocated transmit power, energy efficiency (EE) and spectral efficiency (SE). Simulation results reveal that, the proposed frameworks are incredibly successful in terms of utilization of power budget of users and EE compared to conventional capacity maximization based resource allocation approaches.\",\"PeriodicalId\":23787,\"journal\":{\"name\":\"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering\",\"volume\":\"30 1\",\"pages\":\"105-121\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17706/ijcce.2020.9.3.105-121\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Academy of Science, Engineering and Technology, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17706/ijcce.2020.9.3.105-121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Specific Quality of Service Constrained Optimal Allocation of Transmit Power in Uplink Cognitive OFDMA System
This paper investigates an optimal allocation of transmit power for uplink cognitive OFDMA system. The aim is to construct two optimization frameworks namely, framework-I and II for uplink cognitive OFDMA system that minimizes it’s transmit power while maintaining Quality of Service (QoS). The measures for QoS include SNR threshold for framework-I whereas, for framework-II, it is measured by minimum rate requirement (bits/sec/Hz) to obtain a certain bit error rate (BER). Simulation results reveal the effectiveness of the proposed frameworks. Additionally, for framework-I, effects of different SNR threshold and users’ power budget are observed on the allocation of transmit power. Whereas, for framework-II, effects of different target BER, users’ power budget and minimum rate requirement are observed on the allocation of transmit power. Results are also compared with the results obtained from conventional capacity maximization based resource allocation approaches in terms of allocated transmit power, energy efficiency (EE) and spectral efficiency (SE). Simulation results reveal that, the proposed frameworks are incredibly successful in terms of utilization of power budget of users and EE compared to conventional capacity maximization based resource allocation approaches.