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| Section | Weight | Objectives |
|---|---|---|
| Performance Troubleshooting | 20-25% | - Optimization case studies - Network failure identification and resolution - Troubleshooting tools utilization - Common performance issues diagnosis - Root cause analysis methodologies |
| Radio Network Optimization Techniques | 25-30% | - Interference analysis and mitigation - Parameter tuning best practices - Capacity optimization strategies - Handover optimization - Coverage optimization methods - Load balancing techniques |
| SRAN Architecture and Fundamentals | 15-20% | - Single RAN integration principles - SRAN network architecture overview - SRAN solution components and functions - Radio access concepts and principles |
| Radio Network Performance Monitoring | 20-25% | - Performance monitoring tools and dashboards - KPI definition and measurement - Real-time network monitoring techniques - Threshold configuration and alerting - Performance data collection and analysis |
| SRAN Optimization Tools and Reports | 10-15% | - Automated optimization features - Report generation and interpretation - Nokia NetAct and performance tools - Configuration management for optimization |
>> Latest Nokia SRAN-Radio-Network-Performance-Optimization Exam Test <<
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NEW QUESTION # 29
Evaluate the impact of using MantaRay SON's centralized PCI optimization module compared to distributed SON implementations.
Answer: B
Explanation:
The correct answer is C .
A centralized SON approach has broader network-level visibility than a purely distributed implementation.
For PCI optimization , this is important because PCI conflicts, PCI confusion, and neighbor-related PCI issues are not always local to one cell. They may involve several neighboring cells, multiple layers, and sometimes multiple vendors.
Nokia positions MantaRay SON as a centralized, AI-powered network optimization and automation platform for improving RAN quality, efficiency, and customer experience. Nokia also describes MantaRay SON as supporting multi-supplier/non-real-time RIC functionality in the MantaRay SMO framework.
So compared with distributed SON, centralized PCI optimization can better analyze wider-area PCI relationships and resolve PCI problems across multi-vendor or multi-layer networks.
Therefore, the correct statement is:
Centralized PCI optimization can identify and resolve PCI issues across multi-vendor networks.
NEW QUESTION # 30
The slice type SST value for Extreme Broadband is typically:
Answer: D
Explanation:
The correct answer is B .
In 5G network slicing, SST means Slice/Service Type . It identifies the high-level service category of a network slice.
Typical standardized SST values are:
SST = 1 # eMBB, enhanced Mobile Broadband
SST = 2 # URLLC, Ultra-Reliable Low-Latency Communication
SST = 3 # MIoT/mMTC, Massive IoT or massive Machine Type Communication
SST = 4 # V2X-related slice type
"Extreme Broadband" is normally aligned with eMBB , because it refers to high data rate, high capacity, and broadband user experience.
Therefore, the SST value for Extreme Broadband is:
1.
NEW QUESTION # 31
Which of the following statements about CBRA , or contention-based random access , is correct?
Answer: B
Explanation:
The correct answer is B .
In contention-based random access , the UE chooses a random access preamble by itself from a configured pool of available contention-based preambles. This is typically used when the UE does not yet have a dedicated connection or when the network has not assigned a dedicated preamble.
Because multiple UEs may choose the same preamble at the same time, preamble collision is possible . That is why CBRA requires a contention resolution step.
Option C describes contention-free random access , not CBRA. In contention-free random access, the network assigns a dedicated preamble to the UE, so collision risk is avoided and contention resolution is not required.
Option A is not the correct CBRA principle being tested. RACH false detection can be a receiver/design issue, but it does not define the CBRA procedure.
Option D describes a possible NSA signaling behavior around access failure handling, but it is not the core correct definition of CBRA.
Therefore, the correct CBRA statement is:
The UE autonomously selects a preamble from the configured range and starts the random access procedure.
NEW QUESTION # 32
A slice supporting sensors and smart meters would be categorized as:
Answer: B
Explanation:
The correct answer is A .
Sensors and smart meters are typical massive IoT use cases. They usually involve a very large number of devices sending small amounts of data, often with low mobility and low power requirements.
This type of traffic fits mMTC , or massive Machine Type Communications .
Why the other options are not correct:
URLLC is used for very low-latency and highly reliable services, such as industrial automation, remote control, or mission-critical applications.
eMBB is used for high-throughput broadband services, such as video, fixed wireless access, or enhanced mobile internet.
DNN is not a slice category. It means Data Network Name and identifies the data network the UE connects to, similar to APN in LTE.
Therefore, a slice supporting sensors and smart meters is categorized as:
mMTC.
NEW QUESTION # 33
In the context of mmWave deployments , what is the primary benefit of analog beamforming ?
Answer: C
Explanation:
The correct answer is A .
In mmWave systems, beamforming is essential because FR2 signals suffer from high path loss and blockage.
Analog beamforming uses fewer RF chains than fully digital beamforming, so it is cheaper and less complex in terms of RF hardware, power consumption, and implementation. Research and industry references explain that analog and hybrid beamforming architectures reduce the number of required ADCs/RF chains compared with fully digital beamforming, lowering cost and power complexity.
However, analog beamforming has limitations. It usually forms one beam, or a limited number of beams, at a time from a panel. Supporting multiple independent simultaneous beams and more UEs per sector is more associated with digital or hybrid beamforming, not pure analog beamforming.
Therefore, the primary benefit is:
Low cost and low complexity for coverage at higher mmWave bands.
NEW QUESTION # 34
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