5G RAN NSA Planning Course by MCNS

Customer Tailored

We can tailor the included topics,tech level,and duration of this course right to your team’s technical requirements and needs. - MCNS offers courses to companies, institutions, departments etc and not to individuals as per open courses.

Aimed At

5G RAN NSA Planning is mainly aimed at a technical audience. It is suitable for technical professionals, RAN operators, Radio planning engineers, RAN optimization engineers, Research Institutes, defense sector, who currently are or will be involved in NSA throughput enhancements and 5G NSA deployments.

Prerequisites: Those wishing to take this course should have a good and solid understanding of 5G technology, with emphasis on 5G NR air interface.

Course Review

5G RAN NSA Planning leads the audience into a deep dive towards 5G Non-Stand Alone technology planning principles, both from understanding as well as configuration perspective. It offers an understanding of the opportunities, challenges, and risks that’s needed to exploit and deploy the 5G NSA technology from the throughput perspective. It teaches how to maximize RAN NSA network capacity and enhance data transmission. The course is supported by proper excel dimensioning (calculator) files for practical exercises and case studies.

Course Benefits for individuals (Professionals)

Understanding 5G NSA RAN requirements
Explore 5G RAN coverage and capacity principles
Learn how to plan for cell edge users as well as average cell performance conditions
Understand the principles behind the control channels and reference signals capacity and coverage requirements
Learn how to configure basic parameters
Practice on capacity and coverage planning tools (excel calculators examples) through practical exercises

Course Benefits for your Organization

Equip organization engineers with the necessary knowledge to accomplish difficult and complex tasks related to 5G NR NSA RAN planning.
Keep ahead of competitors in offering well planned and high throughput and quality customers’ 5G services
Identify new revenue streams that can be enabled through 5G
Prepare for future network expansions and quality performance optimization

You will learn

The key points you will learn through this course

5G Radio Technology Review

Basics on Non-Standalone (NSA) Planning

Course Outline

A short brief of your program details & schedule

5G New Radio (NR) Technology Preview

5G Air interface overview
5G NR FR1 and FR2 bands
Scalable numerology
NR frame structure
FDD – TDD modes
NR signals and channels review
Non-Stand-Alone (NSA) architecture
5G NSA Services: eMBB, massive IoT

MIMO &mMIMO Technology overview

LTE to 5G MIMO review
3GPP Massive MIMO standardization
Beam-forming principles
Massive MIMO panels and EiRP
Massive MIMO beamforming gain: Practical approach
Active Antenna Systems; Active Antenna Units

5G Channel Modeling

What is a Mobile Channel model ?– general principles
Non-Line of Sight and Rayleigh modeling
LoS and Rice modeling
Shadow modeling
Site modeling : Macro, micro, pico
Doppler effects and channel models
FR1 Pathloss models (3.6-3.8 GHz, 5-6 GHz)
FR2 Pathloss models for mmW (24-30 GHz, 30-40 GHz, 50-60 GHz)
Example: Link budget analysis overview; various cases (rural, urban, dense urban, O2I)
Exercise: Link Budget calculations using Excel

Uplink Planning

Network quality requirements
Vendor (equipment) UL requirements
Power control factor
Uplink Interference factor: Optional features for Interference mitigation
Coverage planning for PUSCH channel
Coverage planning for PUCCH channel
Coverage planning for signals (SRS, DMRS)
5G NR NSA sector UL capacity estimations – eMBB service
UL NSA & Carrier Aggregation capacity
UL NSA overall throughput estimation (average, cell edge, max) vs SINR
UL Dynamic Spectrum Sharing (DSS) throughput estimation
Exercise: UL capacity estimations using Excel spread-sheet calculator

Downlink Planning

Network quality requirements
Vendor (equipment) DL requirements
Power gain calculation
DL Interference factor: Optional features for Interference mitigation
Coverage planning for PDSCH channel
Coverage planning (including aggregation level) for control channel PDCCH
Coverage planning for signals (PSS, SSS, PBCH, CSI-RS, DMRS)
5G NR NSA sector DL capacity estimations – eMBB service
DL NSA & Carrier Aggregation capacity
DL NSA overall throughput calculation (average, cell edge, max) vs SINR
DL Dynamic Spectrum Sharing (DSS) throughput estimation
Exercise: DL capacity estimations using Excel spread-sheet calculator

Training Format

Instructor-Led Training

On-Site Classroom: 2days

Web delivered (Virtual): 2 days

Excellent and descriptive course material (pdf file) will be provided

FAQ's

What is FD-MIMO and how it relates 5G RAN NSA?

FD-MIMO is one of the possible MIMO implementations allowing antenna systems to form a beam in both horizontal and vertical direction and provide coverage in 3D space. An FD MIMO antenna array has 16, 32 or 64 elements so it could be deemed as a preliminary massive MIMO implementation. In order to consider FD-MIMO as a mMIMO implementation the necessary but not sufficient condition is to implement on the antenna panel enough antenna elements grouped together into sub-arrays. Those increased in number sub-arrays should be properly spaced to each other in order to support the important principle of radio channel deterministic behavior. The sufficient condition however, which is the strongest requirement, is the use of measured channel state rather than the extrapolated channel state information from feedback reports.

How are reference signals used in MIMO technology for 5G RAN NSA?

In legacy MIMO systems, including typical FD-MIMO implementations, gNB adds pre-defined known bit sequences known as pilot or reference signals on the DL in order to train the receiver in UE to measure and model the channel. Hence the channel is measured and estimated according to proper algorithms executed in the UE processor where the amplitude and phase response of the resulting demodulated pilot symbols indicates to the receiving UE the multi-path response and dispersion due to multi-path components of the radio channel. UE then is able to use that information to separate the transmitted data layers (spatially multiplexed streams) from orthogonal paths in the channel and then feedback a channel state report on the UL to the transmitter of gNB. Finally gNB relies on the UE’s feedback in order to extrapolate the channel state and then use the proper precoder to multiplex transmitted data on the DL, fitting the precoded data to the extrapolated channel, with the ultimate goal to facilitate receiver in UE to use its antenna elements to separate the orthogonal signals. But this is a closed-loop procedure putting the burden of channel assessment to the UE’s processor, consuming faster UE battery by simultaneously increasing the UE hardware complexity and upscaling the uplink air interface signaling load due to multiple and frequent channel state reports.

How is channel reciprocity used in mMIMO technology for 5G RAN NSA?

In mMIMO on the contrary, the most common operational principle is the uplink transmission from UE side of proper reference pilot signals to facilitate the gNB to measure the UL channel state and then apply the reciprocal principle considering similar channel state in the DL transmission. Doing so UE is relieved from the burden of interpreting the reference pilot signals and concluding on channel estimation, while all algorithmic channel measurement and estimation processing load is transferred to the gNB. To have a precise reciprocity assumption 5G TDD bands are required, as parts of C-band in sub-6GHz FR1 or mmW bands in FR2. Concluding as long as FD-MIMO antenna panel has a large number of antenna sub-arrays it is not sufficient to upgraded to mMIMO functionality, unless the UL channel estimation measurement is executed.

5G RAN NSA Planning