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Unlocking 5G Spectrum Potential for Intelligent IoT: Opportunities, Challenges and Solutions

Feature Topic


Internet of Things (IoT), one of the hottest trends in technology, is transforming our future by interconnecting everything; humans, vehicles, appliances, utilities, infrastructures, street lights and anything through an intelligent connection. For realization of IoT by 2020, fifth generation (5G) wireless communications network has been considered as an essential unifying fabric that will connect billions of devices in some of the fastest, most reliable and most efficient ways possible whose impact will be revolutionary, reshaping industries and transforming our world. Therefore, 5G is currently attracting extensive research interest from both industry and academia. It is widely agreed that in contrast to 4G, 5G should achieve 1000 times system throughput, 10 times spectral efficiency, higher data rates (i.e., the peak data rate of 10 Gb/s and the user experienced rate of 1Gb/s), 25 times average cell throughput, 5 times reduction in End-to-End (E2E) latency and 100 times higher connectivity density. Among those requirements, the 1000-fold increase in system capacity becomes the most important and may be the most challenging one for 5G systems.

To cope with such challenges, spectrum efficiency through utilization of free and less crowded spectrum resources has been considered as a promising complementary solution by providing flexible and maximal spectrum usage to support the ultra-capacity foreseen by 5G and beyond. Already some technology has been evolving, such as LTE-U/LAA technology has increased the spectrum efficiency of Wi-Fi band through coexistence technology. The practice of extremely high frequency millimeter wave has been already proposed for broadband access and backhaul / fronthaul networks for fast 5G speeds whereas, on the other hand, utilization of the very low frequency band, sub 1-GHz spectrum, is aimed for the IoT for enabling sensor-to-cloud applications.

Although these technological advances ease to meet the forecasted demand on 5G environment, these technologies are still in their infancy. There are many challenges that need to be resolved, such as network coexistence among different radio access technologies, resource sharing and access with legacy devices, Quality of Service (QoS) for users in unlicensed band, environmental and propagation issues, power and cost issues.

This Feature Topic (FT) will bring together academic and industrial researchers to identify and discuss technical challenges and latest results related to spectrum management techniques. Specific topics include, but are not limited to:

  • Interaction of 5G with Intelligent IoT
  • Spectrum sensing, management and mobility for dynamic spectrum management
  • Routing Protocol for dynamic spectrum management for Intelligent IoT
  • Cross-layer design for dynamic spectrum management and Intelligent IoT
  • Traffic prediction and allocation strategies for dynamic spectrum allocation
  • Cooperative dynamic spectrum management with Intelligent IoT
  • Shared use of unlicensed spectrum for dynamic spectrum management
  • Cognitive Radio in 5G Networks in support of Intelligent IoT
  • Co-existence of licensed and unlicensed spectrum in 5G network.
  • Random matrix theory & mathematical analysis of dynamic spectrum management
  • System-level modeling for dynamic spectrum management
  • Artificial intelligence for dynamic spectrum management
  • Location-awareness for dynamic spectrum management
  • Experimental demonstrations, tests and performance characterization for dynamic spectrum management
  • Business model for dynamic spectrum management
  • Standardization aspects of dynamic spectrum management
  • Regulatory framework of dynamic spectrum management
  • Economy Theory framework for dynamic spectrum management


Muhammad Khalil Afzal
COMSATS Institute of Information Technology, Pakistan

Yousaf Bin Zikria
Yeungnam University, South Korea

Shahid Mumtaz
Instituto de Telecomunicações, Portugal

Ammar Rayes
Cisco System,  San Jose, CA, USA

Anwer Al-Dulaimi
EXFO Electro-Optical Engineering

Mohsen Guizani
University of Idaho, USA