of resource allocation and sharing Building and analysis of resource allocation and sharing model between LTE and NB-IoT subscribers Scientific director: prof. Samuylov K. E. Machnev Egor Andreevich NI-401 Bachelor's degree program Department of Applied Informatics and Probability Theory 02.03.02 «Fundamental informatics and information technology» Moscow 2018

Research objectives Develop an overview of next generation wireless communication systems; Examine the problems of serving critical traffic and NB-IoT traffic; Build a QS model with reservation and dynamic allocation of resources; Develop software for calculating cases of QS with reservation and dynamic resource allocation; Investigate a millimeter-wave wireless network for a deployment scenario in a city. 2/23

Contents of Graduate Work 1. Narrow-Band Internet of Things technology in 5G wireless networks 1.1. Narrow-Band IoT technologies and 5G wireless networks 1.2. Technical aspects of NB-IoT traffic services and research objectives 2. Model of sharing 5G cell resources with NB-IoT traffic 2.1. Model building 2.2. Stationary distribution theorem 2.3. Calculation method Simulation model of the millimeter range communication system for serving vehicles on the streets of the megalopolis 3.1. Vehicles traffic model description 3.2. Special cases simulation 3/23

Narrow-Band Internet of Things technology in 5G wireless networks (1/2) Fig. 1. General scheme of the model. 4/23

Narrow-Band Internet of Things technology in 5G wireless networks (2/2) Notations: 𝐶 – Total RRUs 𝑏 𝐿 Resource requirement for one LTE demand 𝑏 𝑁 Resource requirement for one NB-IoT demand 𝑅 𝐿 Reserved capacity for LTE system 𝑅 𝑁 Reserved capacity for NB-IoT system 𝑐 Capacity of one fix-size range 𝑐 𝑚 Number of allocated ranges 𝜆 𝐿 – LTE arrival intensity 𝜆 𝑁 NB-IoT arrival intensity 𝜇 𝐿 LTE serving intensity 𝜇 𝑁 NB-IoT serving intensity 𝜌 𝐿 LTE proposed load 𝜌 𝑁 NB-IoT proposed load 5/23

Contents of Graduate Work 1. Narrow-Band Internet of Things technology in 5G wireless networks 1.1. Narrow-Band IoT technologies and 5G wireless networks 1.2. Technical aspects of NB-IoT traffic services and research objectives 2. Model of sharing 5G cell resources with NB-IoT traffic 2.1. Model building 2.2. Stationary distribution theorem 2.3. Calculation method Simulation model of the millimeter range communication system for serving vehicles on the streets of the megalopolis 3.1. Vehicles traffic model description 3.2. Special cases simulation 6/23

State transition diagram (1/2) Stochastic process: 𝑚 𝑡 – number of active NB-IoT sessions at time 𝑡 𝑛(𝑡) – number of active LTE sessions at time 𝑡 {𝑚 𝑡 , 𝑛 𝑡 , 𝑡>0} – stochastic process Fig. 2 Diagram of the transition rates. 7/23

State transition diagram (2/2) Space of system states: 𝜒 := 𝑚≥0, 𝑛≥0 :𝑛𝑑≤𝐶− 𝑅 𝑁𝐵−𝐼𝑜𝑇 , 𝑐 𝑚 ≤𝐶− 𝑅 𝐻2𝐻 , 𝑛𝑑+𝑐 𝑚 ≤𝐶 (1) Local balance equations: &𝑛 𝜇 𝐿 𝑝 𝑛,𝑚 = 𝜆 𝐿 𝑝 𝑛−1,𝑚 , 𝑛>0, 𝑛, 𝑚 ∈𝜒 & 𝑚 𝜇 𝑁 𝑝 𝑛,𝑚 = 𝜆 𝑁 𝑝 𝑛,𝑚−1 , 𝑚>0, 𝑛, 𝑚 ∈𝜒 (2) Stationary distribution of probabilities: 𝑝 𝑛,𝑚 = 𝜌 𝐿 𝑛 𝑛! 𝜌 𝑁 𝑚 𝑚! 𝑛,𝑚 ∈𝜒 𝜌 𝐿 𝑛 𝑛! 𝜌 𝑁 𝑚 𝑚! (3) 8/23

System performance indicators (1/2) LTE blocking space: 𝐵 𝐿 = 𝑘=0 𝑅 𝑁 𝑐 𝑛,𝑚 ∈𝜒 𝑘 :𝑛= 𝐶− 𝑅 𝑁 𝑏 𝐿 𝑘= 𝑅 𝑁 𝑐 +1 𝑆 𝑛,𝑚 ∈𝜒 𝑘 :𝑛= 𝐶−𝑐𝑘 𝑏 𝐿 (4) NB-IoT blocking space: 𝐵 𝑁 = 𝑘=1 𝑆−1 𝑛, 𝑚 ∈ 𝜒 𝑘 :𝑚= 𝑐𝑘 𝑏 𝑁 , 𝑛 𝑏 𝐿 𝑐 = 𝐶−𝑐𝑘 𝑐 𝑛,𝑚 ∈ 𝜒 𝑆 :𝑚= 𝐶− 𝑅 𝐿 𝑐 𝑀 (5) 9/23

System performance indicators (2/2) LTE blocking probability: B L = 𝑘=0 𝑅 𝑁 𝑐 𝑀 𝑝 𝐶− 𝑅 𝑁 𝑏 𝐿 , 𝑘 + 𝑅 𝑁 𝑐 𝑀+1 𝑆𝑀 𝑝 𝐶−𝑐 𝑘 𝑀 𝑏 𝐿 , 𝑘 (6) NB-IoT blocking probability: B N = 𝑛=0 𝑅 𝐿 𝑏 𝐿 𝑝 𝑛, 𝐶− 𝑅 𝐿 𝑐 𝑀 + 𝑛= 𝑅 𝐿 𝑏 𝐿 +1 𝐶− 𝑅 𝑁 𝑏 𝐿 𝑝 𝑛, 𝐶−𝑛 𝑏 𝐿 𝑐 𝑀 (7) 10/23

Numerical analysis (1/3) Initial data: 𝐶 = 100 𝑐 4 𝜆 𝐿 1/5 𝜆 𝑁 1 𝜇 𝐿 6 𝜇 𝑁 15000 𝑅 𝐿 52 𝑅 𝑁 32 Blocking probability for LTE 11/23 Number of LTE devices

Numerical analysis (2/3) Blocking probability for NB-IoT Number of NB-IoT devices 12/23

Numerical analysis (3/3) Blocking probability for LTE Number of NB-IoT devices 13/23

Contents of Graduate Work 1. Narrow-Band Internet of Things technology in 5G wireless networks 1.1. Narrow-Band IoT technologies and 5G wireless networks 1.2. Technical aspects of NB-IoT traffic services and research objectives 2. Model of sharing 5G cell resources with NB-IoT traffic 2.1. Model building 2.2. Stationary distribution theorem 2.3. Calculation method Simulation model of the millimeter range communication system for serving vehicles on the streets of the megalopolis 3.1. Vehicles traffic model description 3.2. Special cases simulation 14/23

System model of mmWave system in outdoor scenario (1/2) Fig. 3. Outdoor communication scheme 15/23

System model of mmWave system in outdoor scenario (2/2) Notations: 𝑤 – Lane width 𝑉 𝑈 Target car speed 𝑑 Distance between APs 𝑉 𝐵 Other cars speed 𝑅 𝑂 Signal-loss area when overlap 𝑅 𝐵 Uninterrupted access area M Degree of connectivity 16/23

APs switching points coordinates (1/2) 𝑀=3 First iteration equation system: &𝐴 𝑃 1 2 +𝐴 𝐶 2 =𝑞 &𝐸 𝑃 4 2 +𝐶 𝐸 2 =𝑞 &𝐴𝐶+𝐶𝐸=1,5𝑑 Switching point 𝑥 coordinate: 𝑥 𝑖 = 5,25 𝑑 2 −4 𝑤 2 3𝑑 +𝑑∗ 𝑖−1 Second iteration equation system: &𝐷 𝐵 2 +𝐵 𝑃 2 2 =𝑞 &𝐷 𝐹 2 +𝐹 𝑃 5 2 =𝑞 &𝐷𝐵+𝐷𝐹=1,5𝑑 Switching point 𝑥 coordinate: 𝑥 𝑖 = 2,25 𝑑 2 +4 𝑤 2 3𝑑 +𝑑∗ 𝑖−1 17/23

APs switching points coordinates (2/2) Fig. 4. Scenario scheme, 𝑴=𝟑 𝑀=2 𝑖≥1 First switching point 𝒙 coordinate: 𝑥 𝑖 = 𝑖−1 ∗𝑑 Second switching point 𝒙 coordinate: 𝑥 𝑖 =0,5𝑑+𝑑∗ 𝑖−1 𝑀=1 Switching point 𝒙 coordinate: 𝑥 𝑖 = 0,25 𝑑 2 +4 𝑤 2 𝑑 +𝑑 𝑖−1 18/23

Use cases simulation (1/2) 19/23

Use cases simulation (2/2) 20/23

Main results The analysis of the QS with reservation and dynamic allocation of resources are done. Formulas for calculating system performance indicators are obtained. Software for modeling the operation of QS with reservation and dynamic allocation of resources has been developed , and a numerical analysis of performance indicators has been carried out. The wireless network operating in the millimeter-wave range for the deployment scenario in a city is investigated. Formulas for use in a software simulator of the system are obtained. 21/23

References Previous researches: Publications: G. P. Basharin, Yu. V. Gaidamaka, and K. E. Samouylov. Mathematical Theory of Teletraffic and Its Application to the Analysis of Multiservice Communication of Next Generation Networks // Automatic Control and Computer Sciences, 2013, Vol. 47, No. 2, pp. 6269. © Allerton Press, Inc., 2013. Vyacheslav Begishev, Vitaly Petrov, Andrey Samuylov, Dmitri Moltchanov, Sergey Andreev, Konstantin Samouylov, and Yevgeni Koucheryavy. Resource Allocation and Sharing for Heterogeneous Data Collection over Conventional 3GPP LTE and Emerging NB-IoT Technologies // Moscow, RUDN University, February 2018. Vyacheslav Begishev, Andrey Samuilov, Dmitri Moltchanov, Konstantin Samuilov. Efficient simulation of street mmWave deployments with 3GPP multi-connectivity // Moscow, RUDN University, January 2018. V. Petrov, A. Samuylov, V. Begishev, D. Moltchanov, S. Andreev, K. Samouylov, Y. Koucheryavy. Vehicle-Based Relay Assistance for Opportunistic Crowdsensing over Narrowband IoT (NB-IoT) // IEEE Internet of Things Journal, Page(s): 1 – 1, Date of Publication: 16 February 2017. Publications: Е. А. Мачнев, В.О. Бегишев. Имитационное моделирование уличных точек доступа, функционирующих на миллиметровом диапазоне частот // Информационно-телекоммуникационные технологии и математическое моделирование высокотехнологичных систем: материалы Всероссийской конференции с международным участием. Москва, РУДН, 16-20 апреля 2018 г. – Москва: РУДН, 2018. – С. 137. 22/23

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