Open Access Open Access  Restricted Access Subscription Access

Optimization of the Spectral Efficiency in WLAN Networks in the 2.4GHz Band Under the Use of Allocation Models


Affiliations
1 Escuela de Ciencias Básicas Tecnología e Ingeniería (ECBTI), Universidad Nacional Abierta y a Distancia; Carrera 27 Nro. 40-43. Bucaramanga, Colombia
 

Background/Objectives: As a result of the proliferation of Access Point (AP) in various environments, it has demonstrated a significant increase in the interference levels betweenadjacent AP Due to sharing of the ISM bands, significantly affecting network performance.The aim of this paper is to propose an optimization model for allocating channels in the 2.4GHz band, supported in the use allocation models. Methods/Statistical Analysis: A scenario consisting of 6 storey building and 24 Access Point (AP) distributed inside was proposed. The optimization model for allocating frequencies in the 2.4 GHz band is represented as a linear programming problem based on an allocation model, which is a variant of transport models. The model seeks to minimize interference between AP and thereby increase SINR levels and spectral efficiency. To determine whether the proposed model (MF) makes a better allocation of channels than the current model (MA), which incorporates policies RRM, a hypothesis test is performed under mean difference for two independent samples, by t tests -student. Topic Relevance: Although there have been several related channel assignment work, no evidence of any optimization model that has considered using allocation models as a strategy for optimizing spectral efficiency was found. In addition, the model offers levels and reduced computational time complexity. Findings: based on the results it was evident that the model proposed optimization (MF) made a better allocation of resources in the frequency domain compared to the current model (MA), reaching an increase of about 15% in SINR average, with 95% confidence. Application / Improvements: The MF model can be considered as a tool in future research related to the design and analysis of wireless networks which use the 2.4GHz band, to assess aspects of performance, efficiency and QoS.
User

  • Sacoto A, Solís J, Novillo F. Algoritmo de Asignación de Canales para Redes de Comunicación Inalámbricas con Acceso Oportunista basado en Algoritmos Genéticos. Sustentación de Trabajo de Graduación, At Guayaquil, Ecuador; 2014.
  • Tramarin F, Vitturi S, Luvisotto M, Zanella A. On the use of IEEE 802.11n for industrial communications. IEEE Transactions on Industrial Informatics. 2016; 12(5):1877– 86. Crossref
  • Ibhaze AE, Imoize AL, Ajose SO, John SN, Ndujiuba CU, Idachaba FE. An empirical propagation model for path loss prediction at 2100MHz in a dense urban environment. Indian Journal of Science and Technology. 2017;10(5):1–9. Crossref
  • Syafei WA. Implementation of K-Best method for MIMO decoder in WLAN 802.11n. 2nd International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE); 2015. p. 417–21. Crossref
  • Abeysekera BAHS, Matsui M, Asai Y, Mizoguchi M. Network controlled frequency channel and bandwidth allocation scheme for IEEE 802.11a/n/ac wireless LANs: RATOP. IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communication (PIMRC); 2014. p. 1041–5.
  • Yeong S-Y, Al-Salihy W, Wan T-C. Indoor WLAN monitoring and planning using empirical and theoretical propagation models. 2010 IEEE 2nd International Conference on Network Applications, Protocols and Services; 2010. p. 165–9.
  • Rajesh A, Pragathi G, Shankar T. Investigation of an Improved adaptive power saving technique for IEEE 802.11ac systems. Indian Journal of Science and Technology. 2016; 9(37):1–7. Crossref
  • Haidar M, Akl R, Al-Rizzo H, Chan Y. Channel assignment and load distribution in a power-managed Wlan. IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications; 2007. p. 1–5. Crossref
  • Zhou K, Jia X, Xie L, Chang Y, Tang X. Channel assignment for WLAN by considering overlapping channels in SINR interference model. IEEE 2012 International Conference on Computing, Networking and Communications (ICNC); 2012. p. 1005–9. Crossref
  • Abu-Tair M, Bhatti SN. Introducing IEEE 802.11ac into existing WLAN deployment scenarios. 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt); 2015. p. 30–5. Crossref
  • Basha PH, Varma PS, Rajesh KS. QoSperformance of IEEE 802.11 in MAC and PHY layer using Enhanced OAR Algorithm. Indian Journal of Science and Technology. 2017; 10(9):1–9. Crossref
  • Chrysikos T, Georgopoulos G, Kotsopoulos S. Attenuation over distance for indoor propagation topologies at 2.4 GHz. IEEE Symposium on Computers and Communications (ISCC); 2011. p. 329–34. Crossref
  • Ravindranath NS, Singh I, Prasad A, Rao VS. Performance evaluation of IEEE 802.11ac and 802.11n using NS3. Indian Journal of Science and Technology. 2016; 9(26):1–9. Crossref
  • Soleymani M, Maham B, Ashtiani F. Analysis of the downlink saturation throughput of an asymmetric IEEE 802.11n-based WLAN. IEEE International Conference on Communications (ICC); 2016. p. 1–6. Crossref
  • Sangolli SV, Jayavignesh T. TCP throughput measurement and comparison of IEEE 802.11 legacy, IEEE 802.11n and IEEE 802.11ac standards. Indian Journal of Science and Technology. 2015; 8(20):1–8. Crossref
  • Salazar JC, Zapata AB. Análisis y Dise-o de Experimentos Aplicados a Estudios de Simulación Analysis and Design of Experiments Applied to Simulation Studies. 2009; 159:249–57.

Abstract Views: 197

PDF Views: 0




  • Optimization of the Spectral Efficiency in WLAN Networks in the 2.4GHz Band Under the Use of Allocation Models

Abstract Views: 197  |  PDF Views: 0

Authors

F. Juan Carlos Vesga
Escuela de Ciencias Básicas Tecnología e Ingeniería (ECBTI), Universidad Nacional Abierta y a Distancia; Carrera 27 Nro. 40-43. Bucaramanga, Colombia
H. Martha Fabiola Contreras
Escuela de Ciencias Básicas Tecnología e Ingeniería (ECBTI), Universidad Nacional Abierta y a Distancia; Carrera 27 Nro. 40-43. Bucaramanga, Colombia
W. Harold Esneider Perez
Escuela de Ciencias Básicas Tecnología e Ingeniería (ECBTI), Universidad Nacional Abierta y a Distancia; Carrera 27 Nro. 40-43. Bucaramanga, Colombia

Abstract


Background/Objectives: As a result of the proliferation of Access Point (AP) in various environments, it has demonstrated a significant increase in the interference levels betweenadjacent AP Due to sharing of the ISM bands, significantly affecting network performance.The aim of this paper is to propose an optimization model for allocating channels in the 2.4GHz band, supported in the use allocation models. Methods/Statistical Analysis: A scenario consisting of 6 storey building and 24 Access Point (AP) distributed inside was proposed. The optimization model for allocating frequencies in the 2.4 GHz band is represented as a linear programming problem based on an allocation model, which is a variant of transport models. The model seeks to minimize interference between AP and thereby increase SINR levels and spectral efficiency. To determine whether the proposed model (MF) makes a better allocation of channels than the current model (MA), which incorporates policies RRM, a hypothesis test is performed under mean difference for two independent samples, by t tests -student. Topic Relevance: Although there have been several related channel assignment work, no evidence of any optimization model that has considered using allocation models as a strategy for optimizing spectral efficiency was found. In addition, the model offers levels and reduced computational time complexity. Findings: based on the results it was evident that the model proposed optimization (MF) made a better allocation of resources in the frequency domain compared to the current model (MA), reaching an increase of about 15% in SINR average, with 95% confidence. Application / Improvements: The MF model can be considered as a tool in future research related to the design and analysis of wireless networks which use the 2.4GHz band, to assess aspects of performance, efficiency and QoS.

References





DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i22%2F122475