KR102293213B1 - Energy High Efficient Call Admission Control Method in 5G Network - Google Patents

Abstract

The present invention relates to a call admission control method for IoT in a 5G network for reducing energy consumption. The call admission control method in a base station of a mobile communication network of the present invention includes the steps of: receiving a service request from a novel user terminal; calculating the minimum power required for an additional service to the novel user terminal; and approving the service to the novel user terminal when surplus power held by the base station is greater than the minimum required power.

Description

5G Network Energy High Efficient Call Admission Control Method in 5G Network

The present invention relates to a call admission control method, and more particularly, to an efficient call admission control method for reducing energy consumption for the Internet of Things (IoT) in a 5G network.

The Internet of Things (IoT) started with the idea of connecting both wireless and wired sensors to an internet network that can be seen in the home, office, or anywhere. Many contributions have been made to this through Radio Frequency Identification (RFID) and electronic tags. The IoT makes it possible to connect anything connectable, from a variety of objects to “smart dust”. The concept is simple. However, there are many problems because "Things" are not usually sophisticated enough to perform application-related communication and processing. Some mobile networks (4G LTE) are used here, such as LTE-M (LTE for Machine Type Communication) and NB-IoT (Narrowband IoT), which are Low Power Wide Area (LPWA) technologies standardized by 3GPP. There are also other already used LPWA technologies such as LoRa and Sigfox. These days, the bitrate and energy consumption as well as the number of connected objects are increasing very rapidly. To this end, the 5th generation cellular network (5G) manages the UDN (Ultra-Dense Network), which requires a lot of energy, but will provide a solution to this problem.

5G technology is fundamentally for outdoor coverage, cost reduction, increased spectral efficiency, bit rate as well as small cell, lower latency, indoor, while ensuring quality of service (QoS) and quality of experience (QoE), especially energy saving, etc. Aim to increase coverage. According to Cisco and Ericsson, 5G technology will have to deal with the number of connected devices projected to reach nearly 50 billion by 2020. As defined in the Next Generation Mobile Networks (NGMN) document for 5G, energy is defined as the number of bits that can be transmitted per joule, and energy is defined as the It is computed across the network, and improving it is an important issue.

Accordingly, an object of the present invention is to provide an efficient call admission control (CAC) method for IoT in 5G New Radio Access (NR) based on minimum energy consumption.

First, to summarize the features of the present invention, a call admission control method in a base station of a mobile communication network according to an aspect of the present invention for achieving the above object, the method comprising: receiving a service request from a new user terminal; calculating a minimum required power required for an additional service to the new user terminal; and approving the service to the new user terminal when the surplus power held by the base station is greater than the minimum required power.

에 기초하여 (P_TX)min이 산출되며, 여기서, D_i와 B_i는 각각 상기 새로운 사용자 단말의 비트 전송률 및 대역폭, I는 기지국이 서비스하는 다른 모든 사용자 단말들에 의한 총 간섭, N₀은 잡음 전력 스펙트럼 밀도, PL_ij는 상기 새로운 사용자 단말과 상기 기지국 사이의 경로 손실이다.In the step of calculating the minimum required power (P _TX )min, Equation

On the basis of the (P _TX) min this is calculated, wherein, D _i and B _i is the total interference, N ₀ due to the new user terminal of bit rate and bandwidth, I is any other user terminal that the base station service each The noise power spectral density, PL _ij, is the path loss between the new user terminal and the base station.

을 기초로 상기 승인 후 접속 사용자 단말들에 서비스를 위한 총 소비전력 (P_T ^BS)new 보다 큰지 여부를 계산하되, 상기 승인 전 상기 기지국의 총 소비 전력 (P_T ^BS)은, 활성 모드에서의 소비 전력(P_BS)에 대한 수학식

을 기초로 계산하며, 여기서, N_TX는 안테나가 적용된 트랜시버들의 개수, N_Sect는 섹터들의 개수, N_C는 캐리어들의 개수, P₀는 쿨링 및 신호 처리에 의한 정적 소비 전력, P_TX는 전송 소비 전력, P_fL 은 피더의 손실로 인한 소비전력, P_PA은 전력 증폭기의 손실로 인한 소비전력, G_TDX는 불연속 전송메커니즘으로 인한 이득이다.In the step of approving the service to the new user terminal, the power held by the base station is,

On the basis of but calculate is greater than the total power consumption (P _T ^BS) new for the service to the connected user terminal after the approval, the approval total power consumption of all the base station (P _T ^BS) is in the active mode, Equation for Power Consumption (P _{BS )}

, where N _TX is the number of transceivers to which the antenna is applied, N _Sect is the number of sectors, N _C is the number of carriers, P ₀ is static power consumption by cooling and signal processing, and P _TX is transmission consumption Power, P _fL is the power consumption due to the loss of the feeder, P _PA is the power consumption due to the loss of the power amplifier, and G _TDX is the gain due to the discontinuous transmission mechanism.

The user terminal may include a mobile device receiving 5G mobile communication service or an IOT object based on M2M communication.

The mobile communication network is a 5G network that applies three frequency bands divided by the base station according to coverage and data rate capacity, and the three frequency bands are a low frequency band of 2 GHz or less, and a band between 2 GHz and 6 GHz. may include an intermediate frequency band of , and a high frequency band of 6 GHz or higher.

The base station may apply a DTX mechanism including an active mode, a sleep mode, or a deep-sleep mode.

According to the call admission control method according to the present invention, energy waste can be avoided by restricting network access of large-scale devices according to constraints on the total power consumed without degrading QoS, efficient for IoT in 5G networks, etc. A call admission control method may be provided.

BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included as a part of the detailed description to help the understanding of the present invention, provide embodiments of the present invention and, together with the detailed description, explain the technical spirit of the present invention.
1 is a diagram illustrating a schematic description of RRC connection/standby, setup, release, and reconfiguration in 5G NR of the present invention.
2 is a diagram for explaining a Heterogeneous-Cloud Radio Access network (H-CRAN) 5G network according to an embodiment of the present invention.
3 is a schematic diagram of a main configuration of a base station (macrocell MRRH/small cell RRH _{k equipment) according to an embodiment of the present invention.}
4 is a flowchart illustrating a call admission control method in a 5G network base station according to an embodiment of the present invention.
5 is a graph for comparing frequency allocation in NOMA and OFDMA.
6 is a diagram for explaining an example of an implementation method of a cell resource management system for processing a call admission control method in a 5G network base station according to an embodiment of the present invention.

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings. In this case, the same components in each drawing are denoted by the same reference numerals as much as possible. In addition, detailed descriptions of already known functions and/or configurations will be omitted. The content disclosed below will focus on parts necessary for understanding operations according to various embodiments, and descriptions of elements that may obscure the gist of the description will be omitted. Also, some components in the drawings may be exaggerated, omitted, or schematically illustrated. The size of each component does not fully reflect the actual size, so the contents described herein are not limited by the relative size or spacing of the components drawn in each drawing.

In describing the embodiments of the present invention, if it is determined that the detailed description of the known technology related to the present invention may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted. In addition, the terms to be described later are terms defined in consideration of functions in the present invention, which may vary according to intentions or customs of users and operators. Therefore, the definition should be made based on the content throughout this specification. The terminology used in the detailed description is for the purpose of describing embodiments of the present invention only, and should not be limiting in any way. Unless explicitly used otherwise, expressions in the singular include the meaning of the plural. In this description, expressions such as “comprising” or “comprising” are intended to indicate certain features, numbers, steps, acts, elements, some or a combination thereof, one or more other than those described. It should not be construed to exclude the presence or possibility of other features, numbers, steps, acts, elements, or any part or combination thereof.

In addition, terms such as first and second may be used to describe various components, but the components are not limited by the terms, and the terms are for the purpose of distinguishing one component from other components. used only as

<Evolution of CAC (Call Admission Control) in Mobile Communication Networks>

Call Admission Control (CAC) aims to determine whether a new call request can be accepted without causing an unacceptable loss of quality of service to the user. From the user's point of view, an ongoing communication interruption (hanging up a call) is more unpleasant than blocking a call. In general, there are two categories of CAC systems in mobile cellular networks: deterministic CAC and probabilistic CAC.

In 3G networks (3G, WCDMA), power control is used to adjust the transmit power of the UE and BS (NodeB) to a minimum level within the required QoS and to make it with minimal interference to other users. Power control is also required to increase the system's capacity, compensate for fading of radio channels, eliminate or reduce short-range effects, and reduce battery consumption. The decision to grant is primarily based on two conditions: mobile calls to networks with power over which the grant cannot control must be rejected, and mobile calls to networks with power over which grants can always be controlled must not be rejected.

With regards to 4G LTE technology, users can simultaneously request and run other services such as web browsing, real-time gaming and streaming video. Different services have different quality requirements. The main criterion for this technology is that the total number of Physical Resource Blocks (PRBs) per Transmission Time Interval (TTI) required by new users (or handover users) and active users of the evolved NodeB (eNodeB) exceeds the number of PRBs in the system. shouldn't For 5G technology, the International Telecommunications Union (ITU) identifies three main categories of use:

1) mMTC (massive Machine Type Communications): As a large-scale machine type communication, communication between multiple objects (devices) with different quality of service requirements. The goal of this category is to counter the exponential increase in the density of connected objects. connected objects such as portable objects, heart monitors, and devices connected to smart homes/smart cities, as well as communications between vehicles and infrastructure.

2) eMBB (Enhanced Mobile Broadband): Enhanced mobile broadband, providing high-speed connectivity outdoors and indoors with uniform quality of service even at the cell edge. Functions related to virtual and augmented reality as well as functions related to video calls can benefit from these technological advances.

3) uRLLC (Ultra-reliable and Low Latency Communications): Ultra-reliable, low-latency communication, very stable communication for critical requests with very low latency to increase response speed. The reliability and responsiveness of 5G networks, such as autonomous vehicles, could enable autonomous vehicles to respond quickly in real time in many situations. Medicine (e-health) and industry (professional applications of connected devices) are also affected.

<RRC state in 5G of the present invention>

Radio Resource Control (RRC) is in charge of main management of signaling messages between a next generation NodeB (gNB) and a user equipment (UE). The main functions of 5G RRC are: 1) connection establishment, re-establishment and RRC connection release, 2) on-demand SIB transmission whenever the UE needs it, 3) RRC connection interruption/resume, 4) measurement, handover related signaling including handover commands etc.

1 is a diagram illustrating a schematic description of RRC connection/standby, setup, release, and reconfiguration in 5G NR of the present invention.

1 , in the 3GPP 38.331 standard, a new state “RRC INACTIVE” is added to NR RRC compared to LTE. RRC status is a solution for optimizing system access, energy saving and mobility. 5G technology should support eMBB, mMTC, and uRLLC services at the same cost and energy consumption per day and per area. Connectivity control of 5G for future services should be flexible and programmable. In order to satisfy the characteristics of these services, a new RRC service state should be introduced for the following main reasons.

1) In order to support the uRLLC service, small packets with very short latency are transmitted with high reliability.

2) Large-scale IoT devices rarely wake up from sleep and send and receive small payloads.

3) The equipment should be in a low-active state and send uplink data and status reports sporadically on the network with a small payload.

4) Equipment needs periodic and sporadic transmission of downlink packets.

The energy consumption of mobile networks is dominated by base stations (BSs), which currently consume about 80% of their total power. The power consumption of each base station depends on its type (eg macro, micro, pico or femto). The implementation of CRAN (separation of base stations between base band units (BBUs)) in 5G will significantly improve energy efficiency and cost savings.

2 is a diagram for explaining a Heterogeneous-Cloud Radio Access network (H-CRAN) 5G network according to an embodiment of the present invention.

As shown in FIG. 2 , in the H-CRAN 5G network according to an embodiment of the present invention, a macro cell controlled by MRRH (Macro Remote Radio Head) equipment links a BBU (Fronthaul)/Backhaul (BBU). Base Band Unit) has a configuration that interworks with the mobile communication core network through the devices of the pool. The macro cell includes radio access base stations such as Remote Radio Heads ( _{RRH k} ) (eg, k is 1 to M) that cover the small cell and mobile base stations (MBS). Fronthaul/backhaul may include a case in which orthogonal frequency-division multiplexing (OFDM) technology is applied to millimeter wave (mmW).

3 is a schematic diagram of a main configuration of a base station (macrocell MRRH/small cell RRH _{k equipment) according to an embodiment of the present invention.}

3, the base station component is divided into two blocks. The first block consists of cooling and microwave links (backhaul), which are common to all sectors of the cell. The second block is dedicated to each sector, which is a power amplifier (PA) that converts power from direct current (DC) to a radio frequency signal (RF), a transmitter (TX), and a series of bits (or symbols) that convert the signal. digital signal processor (DSP).

Power consumption (P _BS ) by the base station BS (macrocell MRRH/small cell RRH _k equipment) can be expressed as [Equation 1]. Here, N _TX is the number of transceivers to which the antenna is applied, N _Sect is the number of sectors, N _C is the number of carriers, P ₀ is static power consumption by cooling and signal processing, P _TX is transmission power consumption, and P _fL is the base station Power consumption due to loss of feeder connecting equipment and antenna, P _PA is power consumption due to loss of power amplifier (PA), and G _TDX is gain due to discontinuous transmission (DTX) mechanism.

[Equation 1]

The DTX mechanism is used to reduce the energy consumption of the base station by entering the sleep mode for a short period in each frame. In this regard, the base station transmits only when needed, otherwise it places the transmitter in a low power state in sleep mode. You can benefit from this mode. At the physical and medium access layers, transmit-related energy is consumed in power amplifiers, low noise amplifiers, coding and decoding algorithms, signal processing, and RF transceiver chains including channel coding and decoding.

[Equation 1] represents the power consumption (P _BS ) in the active mode, and according to the DTX mechanism, the total power consumption P _T ^BS in the base station (macro cell MRRH / small cell RRH _k equipment) is [Equation 1- 1] can be expressed as

[Equation 1-1]

Here, α ₁ , α ₂ , and α ₃ have binary values, respectively, and have a value of 1 in active mode, sleep mode, and deep-sleep mode, respectively, and have a value of 0 when not in the corresponding mode. In addition, P _max is the maximum transmission power in active mode, P _SM is power consumption in the sleep mode, a deep-sleep mode in a mode that consumes only a part (0 <μ <1) of P _SM. For example, in sleep mode, processors for power amplifiers, low noise amplifiers, coding and decoding algorithms, signal processing, RF transceivers, etc. are blocked from operation, and in deep-sleep mode, power devices in addition to processors whose operation is blocked in sleep mode The operation of all peripheral devices, such as the like, may be blocked.

_{After all, when there are M-1 RRH k} (Remote Radio Heads) for the small cell together with the MRRH (Macro Remote Radio Head) equipment in the macro cell, the total power consumption P _T in the macro cell is [Equation 1 - 2], it can be expressed as the sum of power consumption P _T ^MRRH in MRRH and power consumption P _T ^{RRHk by} _{RRH k.} P _T ^MRRH and P _T ^RRHk may be calculated based on [Equation 1-1].

[Equation 1-2]

<Call admission control method with lower energy in 5G technology of the present invention>

The present invention relates to call admission control (CAC) at the RRH level belonging to a macrocell in a Heterogeneous-Cloud Radio Access network (H-CRAN) environment.

Hereinafter, a call admission control method in a 5G network base station according to an embodiment of the present invention will be described in detail with reference to FIG. 4 .

4 is a flowchart illustrating a method for controlling call admission in a 5G network according to an embodiment of the present invention.

First, consider an RRH serving K user terminals UEs. Each UE has a different bit rate with different services and acceptable QoS. Consider the total maximum power of the cell (P _max ^RRH ) and the total power consumed for K UEs (P _r ^RRH ). The present invention proposes an algorithm for handling new call requests while considering energy consumption constraints as a major requirement for new users. Accordingly, it is possible to provide an efficient call admission control method for IoT in a 5G network that can avoid wasting energy by restricting network access of large-scale devices according to constraints on the total power consumed without degrading QoS.

If a new service request for the (k+1)-th UE occurs while the 1-k-th UE is currently receiving the service through the RRH (S101), the cell resource management system of the base station determines the rate and request for the additional service. Calculate the probability of granting it in the cell according to the established QoS. Therefore, in order to allow the cell to join a new UE, the system may _{calculate the minimum power required for the additional service P K+1} ( S102 ). That is, in the radio part between the RRH and the UE, in order to allow the guaranteed bit rate to the user, it is estimated whether the surplus power retained by the RRH is greater than the minimum power required for the additional service (S103). If the total power of the RRH is not exceeded due to this minimum required power added to the total power, the service is granted to this new UE (S104), otherwise it is denied (S105).

As described above, the minimum additional power required for the additional service to the new UE in S102 may be calculated as follows by the cell resource management system of the base station. _{Using Shannon's formula, the bit rate D i required for UE i} (0 < i < K+1), which is a new user terminal of the cell, is calculated as in [Equation 2]. Here, B _i is the bandwidth of _{UE i.}

[Equation 2]

Here, the signal-to-interference-plus-noise ratio SINR _{ij between the receiver UE i} and the base station transmitter j may be expressed as [Equation 3]. where k is each interference link index, P _TX is the transmitted power, PL _ij is the path loss (dB) between the receiver UE _{i and the base station transmitter j, G ij} is the _{beamforming gain between the receiver UE i} and the base station transmitter j , B _i is the bandwidth for _{UE i , and N 0} is the noise power spectral density.

[Equation 3]

where I is the total interference (power) by all other UEs in the cell served by the base station. _{Using [Equation 2], P TX} is calculated from [Equation 3] to [Equation 4].

[Equation 4]

Therefore, in order to serve the UE requiring the required QoS and the minimum bit rate (D _i )min, the cell consumes the _{minimum required power (P TX )min as shown in Equation 5.}

[Equation 5]

PL _ij is mainly determined by the frequency and transmission model used in the cell. So, when the new UE is approved as above _{, the total power consumption (P T} ^BS )new for service to the access user terminals after _{approval in the base station (MRRH/RRH k} ) is as in [Equation 6], the base station before approval It is the sum of the total power consumption (P _T ^BS ) in [Equation 5] and the minimum transmission power (P _TX )min of [Equation 5]. That is, the cell resource management system _{determines whether or not to grant service to UE i} , which is a new user terminal, whether the power held by the base station (RRH) is greater than _{(P T} ^{BS )new based on [Equation 6].} Calculate.

[Equation 6]

This newly connecting UE will _{only be if (P T} ^BS )new does not exceed the maximum power consumed by the associated base station. Otherwise this new UE is denied access to the cell. For example, the maximum power of the MRRH is 20W and the small cell RRH is 200mW. This value depends on the type of BS deployed in the cell. It can be considered that the power consumed for calculation (computing) in the 5G small cell base station consumes almost 50% of the energy. This computational power of 5G small cell base station (RRH) can reach 800W when transmitting large amounts of traffic by deploying large-capacity MIMO (eg 128 antennas). An equation generally used to calculate the fading of a signal is [Equation 7]. Here, L is the power loss (dB), d is the distance between the transmitter and the receiver (km), and f is the frequency of use (MHz).

[Equation 7]

In [Equation 7], for example, the reference frequency f ₀ may be 1 MHz, the reference distance d ₀ may be 1 km, and these reference values may be arbitrarily selected. However, if the reference values are different from the above values, the constant 32.45 is changed to a different value. The result of calculating the path power loss (L) with respect to frequency and distance using [Equation 7] is shown in Table 1 below.

Compared to a smartphone battery, the power consumption of the base station is tripled. Release 15 of 3GPP (the first 5G standard of 3GPP) with core 4G networks to be used for the first deployments of operator mobile networks operates with a signal coding method called orthogonal frequency-division multiplexing (OFDM) consisting of: This involves distributing the transmission of information flows over a number of channels within an assigned frequency band. Carriers are orthogonal to reduce the gap between them and also to prevent signals from interfering with and cancel each other out. This makes it possible, in particular, to increase the bit rate during transmission while maximizing the spectrum.

The bottom line is that each receiver and transmitter must be able to receive and produce a lot of energy at the same time. While 5G will drive data consumption and require many small antennas to connect all objects, we need to be concerned about the fact that it guarantees the propagation of millimeter waves. Fortunately, 5G will be deployed very gradually. First of all, you should pay attention only to the UE, such as a consumer's smartphone, and not necessarily in a high frequency. Thus, by 2021, we will find new, more energy-efficient methods in Release 16 of 3GPP. In this release, it is recommended to use non-orthogonal multiple access (NOMA), in which UEs use carriers of overlapping frequencies in the same spectrum as in FIG. 5 . 5 is a graph for comparing frequency allocation in NOMA and OFDMA.

A working group of the 3GPP Consortium is discussing this topic. However, this may require the operator to update their base station software and change the receiver. Therefore, mobile network operators may incur additional new costs, as base stations require software updates to handle NOMA and require advanced receivers, more processing power, and other hardware upgrades.

<5G frequency spectrum and transmission model of the present invention>

The base station on the 5G network in the present invention divides and applies the following three frequency bands according to the capacity of coverage and data rate.

At the coverage and capacity layer, it is an intermediate frequency band in the band between 2 GHz and 6 GHz (eg 3400-3800 MHz), providing the best compromise between large coverage and high data rates.

1) In the super data layer, it is a high-frequency band using a frequency of 6 GHz or more (eg, between 24.25-29.5 GHz and 37-43.5 GHz), and is for data processing that requires a very high data rate. This corresponds to millimeter frequency (mmWave).

2) In the coverage layer, it is a low frequency band using a frequency of 2 GHz or less (eg, 700 MHz and 1400 MHz), and provides very large coverage.

In the 5G transmission model, the baseband signal is transmitted from the antenna of the base station to the antenna of the UE without physical connections or wires. The transmitted signal typically meets the attenuation problem in the channel between the transmitter and receiver. The strength of the transmitted signal can be greatly reduced as a function of distance due to factors related to the characteristics of the terrain (eg mountains, buildings, trees, etc.). Prediction of signal strength (ie, calculation of path loss) and measurement is very important for mobile radio performance estimation. Therefore, accurate estimation of radio path loss is essential to predict the coverage area (calculated by the coverage radius) and network capacity (number of UEs served or surface area of the covered area, etc.) of a base station.

Therefore, some mathematical algorithms are used to estimate and predict the transmission path loss. Various models may be used, for example, empirical models, semi-deterministic models, and deterministic models may be used. Each model can be adapted to specific conditions in terms of frequency used, type of terrain, high obstacles, etc. These models can be used after appropriate calibration to adjust to the area considered.

In general, the models used for 5G transmission models include exponential models, and the attenuation model indicates that the attenuation is proportional to dn, where d is the distance and n is a parameter that varies with the shape of the area concerned. In the case of wireless communication by radio waves, n is between 2 and 6, and is generally close to 2 outdoors.

<Application of 5G frequency technology of the present invention to IOT>

The above-mentioned UEs may be mobile devices receiving 5G mobile communication services such as smart phones, tablet PCs, game machines, and PDA, but are not limited thereto, and may include things for IOT connected using M2M (Machine to Machine) communication. can The ITU Recommendation (Rec.ITU-T Y.2060) provides an overview of the Internet of Things (IoT). According to the ITU, a thing is defined as an object in the physical world (physical thing) or information world (virtual thing), which can be identified and integrated in a communication network. Describes the concept and scope of the IoT, identifies the basic characteristics and high-level requirements of the IoT, and describes the IoT reference model. It defines IoT as “the global infrastructure of the information society, enabling advanced services by interconnecting (physical and virtual) things based on existing and evolving interoperable information and communication technologies”.

IoT meets security and privacy requirements while making the most of things to serve all kinds of applications by leveraging identification, data capture, processing and communication capabilities. From a broader perspective, IoT can be perceived as a vision with technological and social implications.

IoT is a new concept for sensor-based things that use Internet Protocol (IP) addresses. It can connect to the internet to collect and analyze sensor data and then make decisions automatically.

IoT is a network of connected devices and things to improve the performance of our daily life, and it is a diverse It combines devices with limited resources of a kind. According to medical research studies, about 80% of people over the age of 65 suffer from at least one chronic disease. According to the ITU, a device is defined as equipment with essential communication functions and optional sensing functions, operation, data capture, data storage and data processing functions, etc.

Some mobile networks (4G LTE), such as LPWA technology (Low Power Wide Area) standardized by 3GPP, LTE-M (MTE for Machine Type Communication) and NB-IoT (Narrowband IoT), may be used. There are also other already used LPWA technologies such as LoRa and Sigfox. In LPWAN, base stations are already installed worldwide by Sigfox and LoraAlliance. Therefore, hardware changes will be expensive.

LTE-M and NB-IoT were developed with the following goals: In other words, it was developed with the goal of improved indoor coverage, ultra-low cost devices, low device power consumption, and optimized network architecture. As an NB-IoT device, numerous devices (eg, sensors or actuators) will be applied accordingly.

LTE-M and NB-IoT technologies are called Cellular IoT (CIoT) to distinguish them from other LPWA solutions. In 3GPP Release 14, LTE-M allows a theoretical maximum throughput of 7Mbps on the uplink (UL) and 4Mbps on the downlink (DL) and uses Cat-M2 modules considering the frequency band of 5MHz, whereas NB-IoT uses Cat Using the -N2 module allows a theoretical maximum throughput of 158.5 Kbps on the UL and 127 Kbps on the DL. 5G technology will not only enhance existing cellular use cases, but also expand into new areas of use cases and scenarios. That is, as an extension area, remote control and process automation for large-scale IoT, smart home, smart city, smart transportation, smart grid, smart autonomous and autonomous vehicles, object tracking, mobile virtual reality, aviation and robotics, mission critical control, etc.

The IoT receiving the 5G mobile communication service of the present invention is expected to include numerous devices connected using Machine to Machine (M2M) communication. These devices will frequently and periodically have different requirements and different types of operation in networks to transmit short amounts of data, such as smart meters used in smart grids and advanced instrumentation infrastructures in industrial applications. In the absence of an alert situation, such as a sensor network for environmental monitoring, other devices can store and transmit data measurements in bulk. Existing solutions to meet the increasing demand include deployment of heterogeneous networks including macro cells and small cells (pico cells, femtocells, etc.) distributed antenna systems (DAS) or relay stations for indoor communication.

One of the requirements of many IoT scenarios is that only very small amounts of data are exchanged (transmitted and received) and there are many time intervals during which the devices are not exchanging, so the power consumption of the devices is very low. If the device does not need to immediately respond to the transmitted data, there is no need to keep the radio module running all the time. For example, if it is enough to check for the arrival of IP packets every 30 minutes, you can save energy by turning off most of the time the radio module. The downside is that the device cannot respond to possible requests between confirmation times.

The 3GPP specification covers "High Latency Communication", including Extended Idle Mode Discontinuous Reception (eDRX) and Power Save Mode (PSM) applied to LTE-M and NB-IoT. extended to related functions.

Regarding services, applications and requirements, the IoT market is divided into two categories: mMTC (Massive Machine Type Communication) and uRLLC (Ultra-Reliable and Low Latency Communication). Smart wearables and sensor networks are two examples of industrial areas that fall into the mMTC category. Smart wearables include connected watches as well as sensors embedded in clothing. A common use case is to measure health-related parameters such as body temperature and heart rate.

In the near future, the number of devices per capita will create new requirements for the capacity needed to support these devices over cellular networks providing IoT services. Additionally, the additional cost of connecting wearables should be very low to attract a large number of consumers. Sensor networks relate, for example, to gas, water and electricity meters. Potentially, each home is equipped with many sensors and meters necessary to increase the connectivity of the communication system. Energy meters are much more difficult to provide sufficient capacity because they are associated with stringent coverage requirements that consume radio resources.

The meter can only rely on the energy provided by the battery, which imposes high energy-efficiency requirements for the device to operate for years with a small, inexpensive battery. In addition, uRLLC can be demonstrated in several applications such as autonomous driving, industrial automation and health. Autonomous driving requires a vehicle connected to a cellular communication network. The network must provide ultra-high reliability combined with very low latency.

Thanks to RFID and sensors, the Internet of Things is becoming a reality. However, the integration of these small devices is difficult to achieve because they are not powerful enough to support the protocol TCP/IP and are very energy consuming. This requires the use of a specific gateway, which may include, for example, a connected gateway and the Internet. 5G could play an important role in this area. A cost-effective radio access network solution for increasing mobile data traffic meets a set of requirements. It should also consume less energy while providing more capacity and network coverage. When it is necessary to connect a phenomenal number of objects and mobile devices in an ultra-dense network such as 5G, large numbers of cells (RRH) must be deployed to counteract the bitrate increase with reasonable energy of QoE. Consumption will also increase significantly.

6 is a diagram for explaining an example of an implementation method of a cell resource management system for processing a call admission control method in a 5G network base station according to an embodiment of the present invention.

The system for processing the call admission control method in the base station according to an embodiment of the present invention as described above may be made of hardware, software, or a combination thereof. For example, the cell resource management system of the present invention may be implemented in the form of a computing system 1000 as shown in FIG. 6 having at least one processor for performing the above functions/steps/processes or a server on the Internet.

The computing system 1000 includes at least one processor 1100 , a memory 1300 , a user interface input device 1400 , a user interface output device 1500 , a storage 1600 connected through a bus 1200 , and a network An interface 1700 may be included. The processor 1100 may be a central processing unit (CPU) or a semiconductor device that processes instructions stored in the memory 1300 and/or the storage 1600 . The memory 1300 and the storage 1600 may include various types of volatile or nonvolatile storage media. For example, the memory 1300 may include a read only memory (ROM) 1310 and a random access memory (RAM) 1320 .

Accordingly, the steps of a method or algorithm described in connection with the embodiments disclosed herein may be directly implemented in hardware, a software module, or a combination of the two executed by the processor 1100 . A software module may be a storage/recording medium (i.e., memory 1300 and/or memory 1300) readable by a device, such as a computer, such as RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM. Alternatively, it may reside in storage 1600 . An exemplary storage medium is coupled to the processor 1100 , the processor 1100 capable of reading information (code) from, and writing information (code) to, the storage medium. Alternatively, the storage medium may be integrated with the processor 1100 . The processor and storage medium may reside within an application specific integrated circuit (ASIC). The ASIC may reside within the user terminal. Alternatively, the processor and storage medium may reside as separate components within the user terminal.

As described above, in the present invention, such energy waste can be avoided by restricting network access of large-scale devices according to constraints on the total power consumed without degrading QoS.

As described above, the present invention has been described with specific matters such as specific components and limited embodiments and drawings, but these are provided to help a more general understanding of the present invention, and the present invention is not limited to the above embodiments. , various modifications and variations will be possible without departing from the essential characteristics of the present invention by those of ordinary skill in the art to which the present invention pertains. Therefore, the spirit of the present invention should not be limited to the described embodiments, and all technical ideas with equivalent or equivalent modifications to the claims as well as the claims to be described later are included in the scope of the present invention. should be interpreted as

Claims (6)

In a call admission control method in a base station of a mobile communication network,
receiving a service request from a new user terminal;
calculating a minimum required power required for an additional service to the new user terminal; and
Approving the service to the new user terminal if the surplus power held by the base station is greater than the minimum required power,
The base station applies a DTX mechanism including an active mode, a sleep mode, or a deep-sleep mode,
In the step of approving the service to the new user terminal,
The power possessed by the base station is,

Calculate whether or not it is greater than the _{total power consumption (P T} ^BS )new for the service to the access user terminals after the approval based on the
The total power consumption of the base station before the grant (P _T ^BS ) is the equation

is calculated based on
Here, α ₁ , α ₂ , and α ₃ each have a binary value, have a value of 1 in active mode, sleep mode, and deep-sleep mode, respectively, and have a value of 0 when not in the corresponding mode,
P _max is the maximum transmission power consumption in active mode, P _SM is the power consumption in sleep mode, and deep-sleep mode is _{a mode in which only a part of P SM} (0<μ<1) is consumed,
N _TX is the number of transceivers to which the antenna is applied, N _Sect is the number of sectors, N _C is the number of carriers, P ₀ is the static power consumption by cooling and signal processing, P _TX is the transmission power consumption, P _fL is the loss of the feeder The power consumption due to , P _PA is the power consumption due to the loss of the power amplifier, G _TDX is the gain due to the DTX transmission mechanism, call admission control method at the base station. According to claim 1,
In the step of calculating the minimum required power (P _TX )min, Equation

Based on (P _TX )min is calculated,
Here, D _i and B _i are the bit rate and bandwidth of the new user terminal, I is the total interference by all other user terminals serviced by the base station, N ₀ is the noise power spectral density, and PL _ij is the new user terminal and a method for controlling call admission in a base station that is a path loss between the base station and the base station. delete According to claim 1,
The user terminal, a mobile device receiving a 5G mobile communication service or a call admission control method in a base station including a thing for IOT based on M2M communication. According to claim 1,
The mobile communication network is a 5G network that applies three frequency bands divided by the base station according to coverage and data rate capacity, and the three frequency bands are a low frequency band of 2 GHz or less, and a band between 2 GHz and 6 GHz. A method for controlling call admission in a base station including an intermediate frequency band of , and a high frequency band of 6 GHz or higher. delete

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