Performance of Offloading Strategies in Collocated Deployments of Millimeter Wave NR-U Technology

5G New Radio (NR) technology operating in millimeter wave (mmWave) band is expected to be utilized in areas with high and fluctuating traffic demands such as city squares, shopping malls, etc. The latter may result in quality of service (QoS) violations. To deal with this challenge, 3GPP has recently proposed NR unlicensed (NR-U) technology that may utilize 60 GHz frequency band. In this paper, we investigate the deployment of NR-U base stations (BS) simultaneously operating in licensed and unlicensed mmWave bands in presence of competing WiGig traffic, where NR-U users may use unlicensed band as long as session rate requirements are met. To this aim, we utilize the tools of stochastic geometry, Markov chains, and queuing systems with random resource requirements to simultaneously capture NR-U/WiGig coexistence mechanism and session service dynamics in the presence of mmWave-specific channel impairments. We then proceed comparing performance of different offloading strategies by utilizing the eventual session loss probability as the main metric of interest. Our results show non-trivial behaviour of the collision probability in the unlicensed band as compared to lower frequency systems. The baseline strategy, where a session is offloaded onto unlicensed band only when there are no resources available in the licensed one, leads to the best performance. The offloading strategy, where sessions with heavier-than-average requirements are immediately directed onto unlicensed band results in just $2-5\%$ performance loss. The worst performance is observed when sessions with smaller-than-average requirements are offloaded onto unlicensed band.acceptedVersionPeer reviewe

Spectrum Coexistence Mechanisms for Mobile Networks in Unlicensed Frequency Bands

Mobile network operators have historically experienced increasing traffic loads at a steady pace, which has always strained the available network capacity and claimed constantly for new methods to increase the network capacity. A key solution proposed to increase the available spectrum is the exploitation of the unlicensed spectrum in the 5 GHz bands, predominantly occupied by Wi-Fi technology. However, an uncontrolled deployment of mobile networks in unlicensed bands could potentially lead to a resource starvation prob lem for Wi-Fi networks and therefore degrade their performance significantly. To address this issue, the 3rd Generation Partnership Project (3GPP) standardised the Long Term Evolution Unlicensed (LTE-U) and Licensed Assisted Access (LAA) technologies. The main philosophy of these technologies is to allow mobile operators to benefit from the vast amount of available spectrum in unlicensed bands without degrading the performance of Wi-Fi networks, thus enabling a fair coexistence. However, the proposed coexistence mechanisms have been proven to provide very limited guarantees of fairness, if any at all. This thesis proposes several improvements to the 3GPP coexistence mechanisms to en able a truly fair coexistence between mobile and Wi-Fi networks in unlicensed bands. In particular, various methods are proposed to adjust the transmission duty cycle in LTE-U and to adapt/select both the waiting and transmission times for LAA. The main novelty of this work is that the proposed methods exploit the knowledge of the existing Wi-Fi activity statistics to tune the operating parameters of the coexistence protocol (duty cycle, contention window size and its adaptation, transmission opportunity times, etc.), optimise the fairness of spectrum coexistence and the performance of mobile networks. This research shows that, by means of a smart exploitation of the knowledge of the Wi-Fi activity statistics, it is possible to guarantee a truly fair coexistence between mobile and Wi-Fi systems in unlicensed bands. Compared to the 3GPP coexistence mechanisms, the proposed methods can attain a significantly better throughput performance for the mobile network while guaranteeing a fair coexistence with the Wi-Fi network. In some cases, the proposed methods are able not only to avoid degradation to the Wi-Fi network but even improve its performance (compared to a coexistence scenario between Wi-Fi networks only) as a result of the smart coexistence mechanisms proposed in this thesis. The proposed methods are evaluated for the 4G LTE standard but are similarly applicable to other more recent mobile technologies such as the Fifth Generation New Radio in Unlicensed bands (5G NR-U)

URLLC for 5G and Beyond: Requirements, Enabling Incumbent Technologies and Network Intelligence

The tactile internet (TI) is believed to be the prospective advancement of the internet of things (IoT), comprising human-to-machine and machine-to-machine communication. TI focuses on enabling real-time interactive techniques with a portfolio of engineering, social, and commercial use cases. For this purpose, the prospective 5{th} generation (5G) technology focuses on achieving ultra-reliable low latency communication (URLLC) services. TI applications require an extraordinary degree of reliability and latency. The 3{rd} generation partnership project (3GPP) defines that URLLC is expected to provide 99.99% reliability of a single transmission of 32 bytes packet with a latency of less than one millisecond. 3GPP proposes to include an adjustable orthogonal frequency division multiplexing (OFDM) technique, called 5G new radio (5G NR), as a new radio access technology (RAT). Whereas, with the emergence of a novel physical layer RAT, the need for the design for prospective next-generation technologies arises, especially with the focus of network intelligence. In such situations, machine learning (ML) techniques are expected to be essential to assist in designing intelligent network resource allocation protocols for 5G NR URLLC requirements. Therefore, in this survey, we present a possibility to use the federated reinforcement learning (FRL) technique, which is one of the ML techniques, for 5G NR URLLC requirements and summarizes the corresponding achievements for URLLC. We provide a comprehensive discussion of MAC layer channel access mechanisms that enable URLLC in 5G NR for TI. Besides, we identify seven very critical future use cases of FRL as potential enablers for URLLC in 5G NR