Araştırma Makalesi
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CİHAZDAN CİHAZA HABERLEŞMEDE GİRİŞİM GİDERİMİ YÖNTEMLERİNİN PERFORMANS KARŞILAŞTIRILMASI

Yıl 2020, , 1019 - 1030, 25.12.2020
https://doi.org/10.21923/jesd.733431

Öz

Bu çalışmada, cihazdan cihaza (D2D) haberleşme çiftleri arasında, hücresel kullanıcılar arasında ve D2D çifti ile hücresel kullanıcılar arasında oluşan girişim problemlerini gidermeyi amaçlayan, iki farklı sistem modeli analiz edilmektedir. İlk incelenen sistem modeli, eşit güç kontrolü ve kısıtlamalar kullanılarak gerçeklenen parçacık sürü optimizasyonu (PSO) tabanlı kaynak tahsisi ve mod seçimidir. Bu yöntemle mevcut alt kanalların verimli ve optimal şekilde kullanılması, en yüksek seviyeli toplam kullanıcı hızının elde edilmesi sağlanmaktadır. İlave olarak, kullanıcı sayısı, yol kaybı üssü, yol kaybı değeri, iterasyon sayısı, alt kanal sayısı gibi toplam kullanıcı hızını etkileyen faktörler de değerlendirilmektedir. Analiz edilen diğer sistem modelinde, hücresel kullanıcıların D2D kullanıcı çiftine oluşturdukları girişim için bir eşik seviyesi belirlenmektedir. Eşik seviyesi değeri ile oluşturulan girişim sınırlı alan için üzerinde çalışılan ikinci sistem modeli ile girişim azaltma ve toplam kullanıcı hızını, kaynak tahsisi ve mod seçimi yöntemine göre yükseltme başarımı sağlanmaktadır. Her iki sistem modeli için, hücresel kullanıcı sayısı temel alınarak, toplam kullanıcı hızları karşılaştırılmaktadır. Karşılaştırma sonucunda girişim sınırlı alan sistem modelinin girişim gideriminde kaynak tahsisi ve mod seçimi modeline göre daha etkili olduğu görülmüştür. Girişim sınırlı alan sistem modelinde, girişim sınırlı alana hücresel kullanıcılardan bazıları dahil olmadığı için kapasite kaybına neden olmaktadır. Kaynak tahsisi ve mod seçiminde kapasite kaybı gerçekleşmemektedir.

Kaynakça

  • Agnew R. P., 1962. Calculus, Analytic Geometry and Calculus, with Vectors. McGraw-Hill Book Company.
  • Akbulut İ., 2009. Parçacık Sürü Optimizasyonu ile Anten Tasarımı, İstanbul Teknik Üniversitesi, İstanbul.
  • Asadi A., Mancuso V., and Wang Q., 2014. A survey on device-to-device communication in cellular Networks. IEEE Communications Surveys and Tutorials, 16( 4), 1801–1819.
  • Basgumus A., Namdar M., Yilmaz G., and Altuncu A., 2015. Performance Comparison of the Differential Evolution and Particle Swarm Optimization Algorithms in Free-Space Optical Communications Systems. Advances in Electrical and Computer Engineering, 15(2), 17–22.
  • Chen L., Chen X., Yang D., Zeng M., and Zhang X., 2012. Downlink Resource Allocation for Device-to-Device Communication Underlaying Cellular Networks. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 232–237.
  • Deng H., Ge N., and Tao X. M., 2012. Joint Mode Selection and Resource Allocation for Cellular Controlled Short-Range Communication in OFDMA Networks. IEEE Transactions on Communications, E9 5-B (3), 1023- 1026.
  • Engin B., 2015. Klasik ve ağ kodlamalı OFDMA sistemlerde alt-taşıyıcı atama, Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi, İstanbul.
  • Ghavami M., Kohno R., and Michael L.B., 2004. Ultra wideband signals and systems in communication Engineering. Wiley.
  • Hou X., Liu F., and Liu Y., 2017. Capacity gain analysis for underlaying full-duplex D2D communications with a novel interference management scheme. 28th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) , 1–5.
  • Jiang Y., Liu Q., Zheng F., Gao X., and You X., 2016. Energy efficient joint resource allocation and power control for D2D communications. IEEE Transactions on Vehicular Technology, 65 (8), 6119–6127.
  • Mahmood K., 2014. Mode Selection Rules For Device to Device Communications: Design Criteria and Performance Metrics, M.Sc. thesis, Istanbul Technical University, Istanbul.
  • Min H., Lee J., Park S., and Hong D., 2011. Capacity Enhancement Using an Interference Limited Area for Device-to-Device Uplink Underlaying Cellular Networks. IEEE Transactions on Wireless Communications, 10 (12), 3995–4000.
  • Mingan Y., and Cetin B. K., 2017. Comparing resource sharing methods for device-to-device communication in cellular Networks. 25th Signal Processing and Communications Applications Conference (SIU), 1-4.
  • Pang H., Wang P., Wang X., Liu F., and Van N. N., 2013. Joint mode selection and resource allocation using evolutionary algorithm for device-to-device communication underlaying cellular networks. Journal of Communication, 8 (11), 751–757.
  • Rappaport T., 2001. Wireless Communications: Principles and Practice, Prentice Hall.
  • Su L., Ji Y. S., Wang P., and Liu F. Q., 2013. Resource allocation using particle swarm optimization for D2D communication underlay of cellular networks. in Wireless Communications and Networking Conference (WCNC), 129 -133.
  • Sun S., and Shin Y., 2014. Resource Allocation for D2D Communication Using Particle Swarm Optimization in LTE Networks. International Conference on Information and Communication Technology Convergence, 371–376.
  • Universal Mobile Telecommunications System (UMTS), 1998. Selection procedures for the choice of radio transmission technologies of the UMTS. 3GPP TR 30. 03U, version 3. 2. 0.
  • Wachowiak M. P., Smolikova R., Zheng Y. F., Zurada J. M., and Elmaghraby A. S. (2004). An approach to multimodal biomedical image registration utilizing particle swarm optimization.IEEE Transactions on Evolutionary Computation,8, pp. 289–301.
  • Yoo T., and Goldsmith A., 2006. On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming. IEEE Journal on Selected Areas in Communications, 24 (3), 528–541.
  • Zhang R., and Liang Y. C., 2008. Exploiting multiantennas for opportunistic spectrum sharing in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2 (1), 88–102.

PERFORMANCE COMPARISON OF INTERFERENCE MITIGATION METHODS IN DEVICE-TO-DEVICE COMMUNICATION

Yıl 2020, , 1019 - 1030, 25.12.2020
https://doi.org/10.21923/jesd.733431

Öz

In this study, two different system models are analyzed which aim to mitigate interference problems between device-to-device (D2D) communication pairs, cellular users, cellular users and D2D pair. The first system model examined is the particle swarm optimization (PSO) based resource allocation and mode selection using equal power control and constraints. With this method, it is ensured that the existing subchannels are used efficiently and optimally, and the highest total throughput is obtained. Additionally, the factors affecting the total throughput, such as number of users, path loss exponent, path loss value, number of iterations, number of subchannels, are also evaluated. In the other system model analyzed, a threshold level is determined for the interference that cellular users create to the D2D user pair. For the interference-limited area created with the threshold level value, the second system model studied is used to reduce the interference reduction and increase the total throughput according to the resource allocation and mode selection method. For both system models, total throughputs are compared based on the number of cellular users. As a result of the comparison, it has been observed that the interference-limited area system model is more effective in interference mitigation than the resource allocation and mode selection model. In the interference-limited area system model, the interference-limited area causes loss of capacity as some of the cellular users are not included. There is no capacity loss in the resource allocation and mode selection.

Kaynakça

  • Agnew R. P., 1962. Calculus, Analytic Geometry and Calculus, with Vectors. McGraw-Hill Book Company.
  • Akbulut İ., 2009. Parçacık Sürü Optimizasyonu ile Anten Tasarımı, İstanbul Teknik Üniversitesi, İstanbul.
  • Asadi A., Mancuso V., and Wang Q., 2014. A survey on device-to-device communication in cellular Networks. IEEE Communications Surveys and Tutorials, 16( 4), 1801–1819.
  • Basgumus A., Namdar M., Yilmaz G., and Altuncu A., 2015. Performance Comparison of the Differential Evolution and Particle Swarm Optimization Algorithms in Free-Space Optical Communications Systems. Advances in Electrical and Computer Engineering, 15(2), 17–22.
  • Chen L., Chen X., Yang D., Zeng M., and Zhang X., 2012. Downlink Resource Allocation for Device-to-Device Communication Underlaying Cellular Networks. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 232–237.
  • Deng H., Ge N., and Tao X. M., 2012. Joint Mode Selection and Resource Allocation for Cellular Controlled Short-Range Communication in OFDMA Networks. IEEE Transactions on Communications, E9 5-B (3), 1023- 1026.
  • Engin B., 2015. Klasik ve ağ kodlamalı OFDMA sistemlerde alt-taşıyıcı atama, Yüksek Lisans Tezi, İstanbul Teknik Üniversitesi, İstanbul.
  • Ghavami M., Kohno R., and Michael L.B., 2004. Ultra wideband signals and systems in communication Engineering. Wiley.
  • Hou X., Liu F., and Liu Y., 2017. Capacity gain analysis for underlaying full-duplex D2D communications with a novel interference management scheme. 28th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) , 1–5.
  • Jiang Y., Liu Q., Zheng F., Gao X., and You X., 2016. Energy efficient joint resource allocation and power control for D2D communications. IEEE Transactions on Vehicular Technology, 65 (8), 6119–6127.
  • Mahmood K., 2014. Mode Selection Rules For Device to Device Communications: Design Criteria and Performance Metrics, M.Sc. thesis, Istanbul Technical University, Istanbul.
  • Min H., Lee J., Park S., and Hong D., 2011. Capacity Enhancement Using an Interference Limited Area for Device-to-Device Uplink Underlaying Cellular Networks. IEEE Transactions on Wireless Communications, 10 (12), 3995–4000.
  • Mingan Y., and Cetin B. K., 2017. Comparing resource sharing methods for device-to-device communication in cellular Networks. 25th Signal Processing and Communications Applications Conference (SIU), 1-4.
  • Pang H., Wang P., Wang X., Liu F., and Van N. N., 2013. Joint mode selection and resource allocation using evolutionary algorithm for device-to-device communication underlaying cellular networks. Journal of Communication, 8 (11), 751–757.
  • Rappaport T., 2001. Wireless Communications: Principles and Practice, Prentice Hall.
  • Su L., Ji Y. S., Wang P., and Liu F. Q., 2013. Resource allocation using particle swarm optimization for D2D communication underlay of cellular networks. in Wireless Communications and Networking Conference (WCNC), 129 -133.
  • Sun S., and Shin Y., 2014. Resource Allocation for D2D Communication Using Particle Swarm Optimization in LTE Networks. International Conference on Information and Communication Technology Convergence, 371–376.
  • Universal Mobile Telecommunications System (UMTS), 1998. Selection procedures for the choice of radio transmission technologies of the UMTS. 3GPP TR 30. 03U, version 3. 2. 0.
  • Wachowiak M. P., Smolikova R., Zheng Y. F., Zurada J. M., and Elmaghraby A. S. (2004). An approach to multimodal biomedical image registration utilizing particle swarm optimization.IEEE Transactions on Evolutionary Computation,8, pp. 289–301.
  • Yoo T., and Goldsmith A., 2006. On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming. IEEE Journal on Selected Areas in Communications, 24 (3), 528–541.
  • Zhang R., and Liang Y. C., 2008. Exploiting multiantennas for opportunistic spectrum sharing in cognitive radio networks. IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2 (1), 88–102.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Elektrik Mühendisliği
Bölüm Araştırma Makaleleri \ Research Articles
Yazarlar

Meryem Taşer Bu kişi benim 0000-0003-3577-3495

Mustafa Namdar 0000-0002-3522-4608

Arif Başgümüş 0000-0002-0611-3220

Yayımlanma Tarihi 25 Aralık 2020
Gönderilme Tarihi 7 Mayıs 2020
Kabul Tarihi 23 Eylül 2020
Yayımlandığı Sayı Yıl 2020

Kaynak Göster

APA Taşer, M., Namdar, M., & Başgümüş, A. (2020). CİHAZDAN CİHAZA HABERLEŞMEDE GİRİŞİM GİDERİMİ YÖNTEMLERİNİN PERFORMANS KARŞILAŞTIRILMASI. Mühendislik Bilimleri Ve Tasarım Dergisi, 8(4), 1019-1030. https://doi.org/10.21923/jesd.733431