• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.766-777
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• 2021

This paper presents an improved scheme for detection of the physical broadcast channel (PBCH) in long-term evolution (LTE)-based fifth-generation (5G) multimedia broadcast and multicast services (MBMS) and 5G new radio (NR) for cellular broadcast. In the time domain, by combining the correlations between the received signal and primary synchronization signal (PSS) within all SS/PBCH blocks, the frame synchronization and the start position of the SS/PBCH blocks can be obtained. In this paper, to improve the detection performance of PBCH for 5G NR, a combining scheme of PBCH signals within a frame is proposed. In addition, the performance of the proposed detection scheme is evaluated and the performance is compared with the conventional scheme for PBCH detection of LTE-based 5G MBMS. The simulation results show that the detection performance of PBCH for 5G NR is improved by combining the PBCH signals and outperforms LTE-based 5G MBMS under the additive white Gaussian noise (AWGN), fixed, and mobile environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2668-2717
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• 2021

Demands for high-speed wireless data services grow rapidly. It is a big challenge to increasing the network capacity operating on licensed spectrum resources. Unlicensed spectrum cellular networks have been proposed as a solution in response to severe spectrum shortage. Licensed Assisted Access (LAA) was standardized by 3GPP, aiming to deliver data services through unlicensed 5 GHz spectrum. Furthermore, the 3GPP proposed 5G New Radio-Unlicensed (NR-U) study item. On the other hand, artificial intelligence (AI) has attracted enormous attention to implement 5G and beyond systems, which is known as Intelligent Radio (IR). To tackle the challenges of unlicensed spectrum networks in 4G/5G/B5G systems, a lot of works have been done, focusing on using Machine Learning (ML) to support resource allocation in LTE-LAA/NR-U and Wi-Fi coexistence environments. Generally speaking, ML techniques are used in IR based on statistical models established for solving specific optimization problems. In this paper, we aim to conduct a comprehensive survey on the recent research efforts related to unlicensed cellular networks and IR technologies, which work jointly to implement 5G and beyond wireless networks. Furthermore, we introduce a positioning assisted LTE-LAA system based on the difference in received signal strength (DRSS) to allocate resources among UEs. We will also discuss some open issues and challenges for future research on the IR applications in unlicensed cellular networks.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.260-263
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• 2021

3GPP (3rd generation partnership project)는 5G 요구 조건을 충족시키기 위해 release 16 에서 FeMBMS (further evolved MBMS)를 LTE 기반 5G MBMS 로 개선하였다. 이어서, 현재 개발 중인 release 17 에서 NR 기반의 디지털 방송을 위한 NR MBS (multimedia broadcast services)가 논의되고 있다. 본 논문에서는 LTE (long term evolution) 기반 5G MBMS (fifth generation multimedia broadcast & multicast services)와 5G NR (fifth generation new radio)의 PBCH (physical broadcast channel) 에 대한 송수신기 구조를 설명하고, 성능을 평가한다. 본 논문에서는 가산 백색 가우시안 잡음(additive white Gaussian noise: AWGN) 및 고정 환경 하에서 LTE 기반 5G MBMS 와 5G NR 에 대한 PBCH 의 성능을 비교한다.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.10
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• pp.299-308
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• 2023

As the spectrum shortage problem has accelerated by the emergence of various services, New Radio-Unlicensed (NR-U) has appeared, allowing users who communicated in licensed bands to communicate in unlicensed bands. However, NR-U network users reduce the performance of Wi-Fi network users who communicate in the same unlicensed band. In this paper, we aim to simultaneously maximize the fairness and throughput of the unlicensed band, where the NR-U network users and the WiFi network users coexist. First, we propose an optimal power allocation scheme based on Monte Carlo Policy Gradient of reinforcement learning to maximize the sum of rates of NR-U networks utilizing rate-splitting multiple access in unlicensed bands. Then, we propose a channel occupancy time division algorithm based on sequential Raiffa bargaining solution of game theory that can simultaneously maximize system throughput and fairness for the coexistence of NR-U and WiFi networks in the same unlicensed band. Simulation results show that the rate splitting multiple access shows better performance than the conventional multiple access technology by comparing the sum-rate when the result value is finally converged under the same transmission power. In addition, we compare the data transfer amount and fairness of NR-U network users, WiFi network users, and total system, and prove that the channel occupancy time division algorithm based on sequential Raiffa bargaining solution of this paper satisfies throughput and fairness at the same time than other algorithms.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.593-595
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• 2020

본 논문에서는 5G NR 시스템을 위한 동기 신호를 이용한 cell ID 검출 방법에 대한 성능을 비교하였다. 5G NR(fifth-generation new radio) 시스템의 송신기는 SS/PBCH (synchronization signal/physical broadcast channel) 블록을 송신하며, 수신기는 수신된 SS/PBCH 블록을 이용하여 주파수 및 타이밍 오프셋 (frequency and timing offset)을 추정 할 수 있으며, cell ID (cell identity)는 PSS (primary synchronization signal)와 SSS (secondary synchronization signal)를 통해 검출할 수 있다. 본 논문에서는 cell ID 를 검출할 수 있는 방법으로서 2-stage 디코딩 방법과 결합 최대우도 결정 규칙 (joint maximum-likelihood decision rule: joint ML) 디코딩 방법을 사용하였다. Joint ML 디코딩 방법은 2-stage 디코딩 방법에 비해 더 좋은 검출 성능을 보이지만, 복잡도 측면에서는 2-stage 디코딩 방법이 joint ML 디코딩 방법에 비해 더 낮은 복잡도를 갖는 것을 확인하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.634-636
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• 2020

본 논문에서는 딥러닝 (deep learning) 방식을 이용한 5G NR (fifth-generation new radio)의 cell ID (cell identity) 검출 기법을 구현하였다. 5G NR 시스템의 단말 (user equipment)은 초기 접속 (initial access)과정에서 PSS (primary synchronization signal)와 SSS (secondary synchronization signal)을 이용한 동기 획득 및 cell ID 검출이 필요하다. 본 논문에서는 분류 기법 기반의 딥러닝 기술을 이용하여 인공 신경망 모델에 PSS 및 SSS 와 cell ID 의 상관 관계를 학습시키고, 학습된 모델의 성능을 제시하였다.

• Electronics and Telecommunications Trends
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• v.34 no.6
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• pp.51-60
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• 2019

As a way to further expand and enable the 5G ecosystem, the $3^{rd}$ Generation Partnership Project (3GPP) is considering the development of a 5G new radio (NR)-based non-terrestrial network (NTN). These NTNs are expected to provide ubiquitous 5G services to user's equipment (especially, in Internet of Things/machine-type communications (IoT/MTC) public safety, and critical communications) by extending service coverage to areas not covered by 5G terrestrial networks. To this end, this NTN is developing scenarios to provide 5G services using spaceborne vehicles, such as geosynchronous and low-Earth orbit satellites, and airborne vehicles, such as unmanned aircraft systems, including high-altitude pseudo-satellites. In addition, various technologies are being studied to satisfy new requirements not considered in 5G NR, such as long propagation delay time, large cell coverage, large Doppler effect, and base station movement. In this paper, we present the scenarios, requirements, technical issues and solutions, and standardization planning for NR-based NTN in 3GPP.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.870-881
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• 2020

This paper presents cell ID (cell identity) detection schemes using PSS/SSS (primary synchronization signal/secondary synchronization signal) for 5G NR (new radio) system and evaluates the detection performance. In this paper, we consider two cell ID detection schemes, i.e. two-stage detection and joint detection schemes. The two-stage detection scheme consists of two stages which estimate a channel gain between a transmitter and receiver and detect the PSS and SSS sequences. The joint detection scheme jointly detects the PSS and SSS sequences. In addition, this paper presents coherent and non-coherent combining schemes. The coherent scheme calculates the correlation value for the total length of the given PSS and SSS sequences, and the non-coherent combining scheme calculates the correlation within each group by dividing the total length of the sequence into several groups and then combines them non-coherently. For the detection schemes considered in this paper, the detection error rates of PSS, SSS and overall cell ID are evaluated and compared through computer simulations. The simulation results show that the joint detection scheme outperforms the two-stage detection scheme for both coherent and non-coherent combining schemes, but the two-stage detection scheme can greatly reduce the computational complexity compared to the joint detection scheme. In addition, the non-coherent combining detection scheme shows better performance under the additive white Gaussian noise (AWGN), fixed, and mobile environments.

• Electronics and Telecommunications Trends
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• v.31 no.6
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• pp.88-96
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• 2016

5G RAN은 4G가 진화된 무선기술(evolved E-UTRA)과 5G 무선기술(New Radio, NR)을 모두 지원하는 새로운 무선액세스 네트워크(New RAN)이며, 코어 네트워크 (EPC and NGC)과 접속되어 5G 시스템(NextGen System)을 구성한다. 본고에서는 5G RAN(Radio Access Network,)을 대상으로, RAN 시설 배치 시나리오, RAN과 CN 간 기능 분배 및 인터페이스, 프런트-홀 네트워크의 전송 용량 및 지연, New RAN과 E-UTRA 간 모빌리티 시나리오 등에 대한 표준 이슈를 살펴본다. 마지막 절에선 RAN의 네트워크 슬라이싱 지원 방안으로 상위레벨 개념의 구조와 절차를 정리한다. 본 문서는 3GPP RAN3 그룹의 기술보고서(TR 38.801)와 SA2 기술보고서(TR 23.799)를 바탕으로 작성되었다.

• ETRI Journal
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• v.45 no.1
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• pp.7-17
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• 2023

The error-rate floor of low-density parity-check (LDPC) codes is attributed to the trapping sets of their Tanner graphs. Among them, fully absorbing sets dominantly affect the error-rate performance, especially for short blocklengths. Efficient methods to identify the dominant trapping sets of LDPC codes were thoroughly researched as exhaustively searching them is NP-hard. However, the existing methods are ineffective for Raptor-like LDPC codes, which have many types of trapping sets. An effective method to identify dominant fully absorbing sets of Raptor-like LDPC codes is proposed. The search space of the proposed algorithm is optimized into the Tanner subgraphs of the codes to afford time-efficiency and search-effectiveness. For 5G New Radio (NR) base graph (BG) 2 LDPC codes for short blocklengths, the proposed algorithm finds more dominant fully absorbing sets within one seventh of the computation time of the existing search algorithm, and its search-effectiveness is verified using importance sampling. The proposed method is also applied to 5G NR BG1 LDPC code and Advanced Television Systems Committee 3.0 type A LDPC code for large blocklengths.