823  Mobile Wireless: Comprehensive Quiz

823.1 Learning Objectives

By the end of this chapter, you will be able to:

  • Validate Electromagnetic Understanding: Apply wave properties to wireless communication
  • Calculate Path Loss: Use FSPL formulas for deployment planning
  • Analyze Spectrum Trade-offs: Compare licensed vs unlicensed spectrum options
  • Apply Channel Selection: Choose optimal channels in congested environments
  • Synthesize Agricultural Deployment: Select technologies for long-range, low-power scenarios

823.2 Prerequisites

Required Chapters: - Cellular Network Architecture - Technology selection - Scenario-Based Analysis - Trade-off reasoning - Mobile Wireless Technologies Basics - Core concepts

Recommended Preparation: - Review link budget calculations - Understand frequency band characteristics - Know regulatory differences (EU vs US)

Estimated Time: 45 minutes

How to approach this quiz: 1. Read each question carefully - details matter 2. Eliminate obviously wrong answers first 3. Calculate when formulas are provided 4. Consider real-world implications

What’s being tested: - Understanding of electromagnetic properties - Ability to calculate path loss - Knowledge of spectrum regulations - Technology selection reasoning

823.3 Quiz 1: Comprehensive Review

Question 1: An IoT device transmits at 868 MHz while another transmits at 2.4 GHz. If both transmit the same power, which statement correctly describes their electromagnetic properties?

Explanation: Using the relationship c = f x lambda, higher frequency results in shorter wavelength. (In quantum terms, E = h f gives energy per photon, but RF link budgets are governed by transmit power, antennas, and path loss - not photon energy.) At 2.4 GHz (2400 MHz), the wavelength is lambda = 3x10^8 m/s / 2.4x10^9 Hz = 0.125 m (12.5 cm). At 868 MHz, the wavelength is lambda = 3x10^8 m/s / 868x10^6 Hz = 0.346 m (34.6 cm). In practice, higher frequency signals typically experience more path loss and are more sensitive to obstacles, so sub-GHz bands often provide better range for the same power/antenna constraints.

Question 2: Calculate the free space path loss (FSPL) for a 2.4 GHz signal traveling 50 meters. Use the formula: FSPL(dB) = 20log10(d_km) + 20log10(f_MHz) + 32.45

Explanation: Using FSPL(dB) = 20log10(d_km) + 20log10(f_MHz) + 32.45 with d = 50m = 0.05 km and f = 2400 MHz: - FSPL = 20log10(0.05) + 20log10(2400) + 32.45 - FSPL = 20(-1.301) + 20(3.380) + 32.45 - FSPL = -26.02 + 67.60 + 32.45 = 74.03 dB

This means the signal strength decreases by 74 dB over 50 meters in free space. In practice, indoor environments add 10-30 dB additional loss due to walls, furniture, and multipath interference. This is why a Wi-Fi router with +20 dBm transmit power might produce a -54 dBm received signal at 50m in an office environment.

Question 3: A smart building deploys sensors throughout a facility with thick concrete walls. Sub-GHz (868 MHz) signals penetrate walls with approximately 5-7 dB loss, while 2.4 GHz experiences 10-15 dB loss. If a sensor 30m away behind 3 concrete walls needs -100 dBm minimum signal, which frequency band requires less transmit power?

Explanation: Let’s calculate the total path loss for each band. First, free space path loss at 30m: - 868 MHz: FSPL = 20log10(0.03) + 20log10(868) + 32.45 = -30.46 + 58.77 + 32.45 = 60.8 dB - 2.4 GHz: FSPL = 20log10(0.03) + 20log10(2400) + 32.45 = -30.46 + 67.60 + 32.45 = 69.6 dB

Then add wall penetration loss (3 walls): - 868 MHz: 60.8 dB + (3 x 6 dB) = 78.8 dB total - 2.4 GHz: 69.6 dB + (3 x 12.5 dB) = 107.1 dB total

To receive -100 dBm, required transmit power: - 868 MHz: Tx = -100 dBm + 78.8 dB = -21.2 dBm (approximately 7.6 uW) - 2.4 GHz: Tx = -100 dBm + 107.1 dB = +7.1 dBm (approximately 5.1 mW)

Difference: 107.1 - 78.8 = 28.3 dB, meaning 868 MHz can use approximately 680x less transmit power to reach the same received power (all else equal). This can dramatically extend battery life in low-power IoT deployments.

Question 4: In 2.4 GHz Wi-Fi, channels are spaced 5 MHz apart but typical channel widths are approximately 20/22 MHz, so many channel numbers partially overlap. Why is channel overlap problematic for Wi-Fi networks?

Explanation: In 2.4 GHz, channel numbers are close together relative to channel width, so “different channels” can still overlap in frequency. When neighboring APs use overlapping channels (e.g., channels 1 and 3), transmissions interfere more often, increasing contention, retries, and latency.

Performance impacts: - More contention/backoff: more devices compete for airtime - More retries/retransmissions: corrupted frames require resending - Higher latency and lower throughput: especially for many small IoT frames

Best practice for multi-AP deployments: - Use a non-overlapping plan in 2.4 GHz (commonly 1/6/11 for 20 MHz operation) and avoid “in-between” channels - Use 5 GHz/6 GHz where possible for more channel options and less congestion - Validate with measurements (channel utilization and RSSI), not just channel number

Question 5: In the electromagnetic spectrum, why do IoT devices primarily use radio frequencies (3 kHz - 300 GHz) rather than visible light or infrared for wireless communication?

Explanation: Radio frequencies are ideal for IoT because they can penetrate walls, reflect around obstacles, and provide omnidirectional coverage without line-of-sight requirements.

Comparison across spectrum:

Radio (3 kHz - 300 GHz): - Penetrates walls, furniture, vegetation - Reflects/diffracts around obstacles - Works through weather (rain, fog) - Omnidirectional antennas possible - Regulated spectrum requires compliance

Infrared (300 GHz - 430 THz): - Line-of-sight only - Blocked by walls, even thin paper - Used for TV remotes, IrDA (obsolete) - Very short range (1-5 meters)

Visible Light (430-750 THz): - Line-of-sight only - Li-Fi uses LED flicker for data - Blocked by any opacity - Extreme directional requirements

Why B is wrong: Radio waves actually have LESS energy per photon than visible light (E = h x f, so lower frequency = lower energy), but this is irrelevant for communication - what matters is propagation characteristics, not photon energy.

Real-world example: A Wi-Fi router in one room can serve devices throughout a house because 2.4 GHz radio penetrates walls. A Li-Fi system would require line-of-sight to every device and fails if you walk between the transmitter and receiver.

Question 6: A campus-wide LoRaWAN deployment in Europe uses the 868 MHz ISM band with a 1% duty cycle limitation. If a sensor transmits a 50-byte packet at 5 kbps data rate, how many packets can it transmit per hour without violating duty cycle regulations? (Assume payload-only and ignore PHY/MAC overhead.)

Explanation: Duty cycle limits restrict the percentage of time a device can transmit to prevent spectrum congestion. Let’s calculate:

Step 1: Calculate transmission time per packet - Packet size: 50 bytes = 400 bits - Data rate: 5 kbps = 5000 bits/second - Transmission time: 400 bits / 5000 bps = 0.08 seconds (80 milliseconds)

Note: This is a simplified estimate. Real LoRaWAN time-on-air depends on spreading factor, coding rate, preamble, headers, and acknowledgements.

Step 2: Apply 1% duty cycle limit - 1% of 1 hour = 3600 seconds x 0.01 = 36 seconds total transmission time allowed - Packets allowed: 36 seconds / 0.08 seconds/packet = 450 packets

Step 3: Verify timing - 450 packets x 80 ms = 36,000 ms = 36 seconds (exactly 1% of 1 hour)

Practical implications: - Packet interval: 3600 seconds / 450 = 8 seconds minimum between packets - For always-on monitoring: Need to aggregate data or use licensed spectrum - For event-driven sensors: Usually acceptable (e.g., door sensors, alarms)

Regional variations: - Europe (ETSI): 1% duty cycle on 868 MHz (some sub-bands allow 10%) - US: no ETSI-style duty cycle limit, but other constraints (power/channel rules) apply - Asia-Pacific: Varies by country and frequency band

This is why LoRaWAN uses adaptive data rates - slower rates increase time-on-air, reducing how often you can transmit under duty-cycle constraints.

Question 7: Compare licensed cellular spectrum (e.g., NB-IoT) versus unlicensed ISM bands (e.g., LoRaWAN) for a smart city deployment with 10,000 parking sensors operating for 10 years. What are the key trade-offs?

Explanation: Licensed cellular (e.g., NB-IoT/LTE-M) and unlicensed LPWAN (e.g., LoRaWAN) are both used for large IoT fleets, but they shift cost and responsibility differently.

Licensed cellular (NB-IoT): - Pros: Operator-managed network and coverage, interference management, mobility support, and sometimes SLAs - Cons: Recurring subscriptions, dependence on carrier coverage/policies, and less control over the network

Unlicensed LPWAN (LoRaWAN): - Pros: No per-device subscription by default, more control over gateways/data, and flexible private deployments - Cons: You must deploy/maintain gateways and backhaul; operation is in shared spectrum with regulatory constraints (duty cycle/LBT) and interference risk

Decision lens: - Scale economics: recurring subscription vs owning infrastructure/operations - Coverage and mobility: carrier footprint/roaming vs your gateway density and placement - Reliability expectations: managed QoS vs best-effort in shared spectrum (design for retries and redundancy)

Question 8: A Wi-Fi network scan reveals 15 access points on channel 6, 8 on channel 1, and 12 on channel 11. When deploying a new access point for IoT devices, which channel should you select and why?

Explanation: In 2.4 GHz, good channel selection tries to minimize both co-channel contention (many APs on the same channel) and adjacent-channel interference (overlapping channels). Based on the scan counts alone, Channel 1 is the best choice here.

Why Channel 1 is correct: - In many deployments using 20 MHz channels (and especially where channels 1-11 are the practical set), 1/6/11 is the common non-overlapping plan - Channel 1 has only 8 networks (vs 15 on ch6, 12 on ch11) - Fewer APs on the same channel usually means less contention for airtime (lower latency and fewer retries)

Why other options are wrong:

Channel 6 (most congested): - 15 networks means high competition - More contenders generally means more backoff, more overhead, and higher latency

Channel 3 (overlapping): - Overlaps significantly with both channel 1 and channel 6 at 20/22 MHz widths - Creates adjacent-channel interference (bad for you and your neighbors)

Channel 14: - Not available in most regulatory domains and often unsupported by devices - Even where present, it is typically limited (e.g., legacy 802.11b-only use)

Advanced consideration - Signal strength matters too: If channel 1 has 8 strong signals (-40 dBm each) but channel 6 has 15 weak signals (-80 dBm each), channel 6 might actually perform better because strong signals dominate airtime more than numerous weak ones. Use Wi-Fi analyzer tools to measure both count AND strength!

Pro tip: Scan over time. Auto-channel selection and daily usage patterns can change congestion, so validate with a short measurement plan (peak vs off-peak).

Question 9: You measure RSSI values of -45 dBm at 5 meters and -65 dBm at 50 meters from a 2.4 GHz access point. The theoretical free space path loss predicts a 20 dB increase (from 20log10 of the 10x distance increase). Why is the observed loss (20 dB) close to theoretical despite being indoors?

Explanation: This scenario demonstrates the complex nature of indoor RF propagation where multipath effects can sometimes improve signal strength.

Why observed loss matches theoretical:

Free space path loss calculation: - Path loss ratio: 20log10(50/5) = 20log10(10) = 20 dB - Predicted RSSI at 50m: -45 dBm - 20 dB = -65 dBm - Observed RSSI at 50m: -65 dBm (Perfect match!)

But wait - what about walls and obstacles?

Indoor environments create multipath propagation: 1. Direct path: Line-of-sight signal (if available) 2. Reflected paths: Signals bouncing off walls, ceilings, furniture 3. Diffracted paths: Signals bending around obstacles

Constructive interference scenario: - Multiple reflected paths arrive at the receiver - If path lengths differ by integer multiples of wavelength, signals add constructively - Combined signal strength can exceed direct path alone - This can compensate for attenuation through obstacles

Real-world variation: - Move receiver 1 meter and RSSI might drop to -75 dBm (destructive interference) - Indoor propagation creates standing wave patterns with “hot spots” and “dead zones” - This is why walking around with a phone shows fluctuating signal bars

Path loss models for indoor: - Free space: FSPL = 20log10(d) + 20log10(f) + 32.45 (baseline) - Indoor: FSPL_indoor = FSPL + n x wall_loss + floor_loss (typically adds 10-30 dB) - But multipath can reduce actual loss by -10 to +10 dB locally

Practical implications: - Never rely on single-point measurements - Take measurements at multiple locations - Expect +/-10 dB variation due to multipath - Design systems with fade margin to handle variations

Question 10: A Zigbee mesh network operates on 2.4 GHz channel 15 (2.425 GHz center frequency). A nearby Wi-Fi network on channel 3 (2.422 GHz center frequency) is causing interference. Why does this occur when they’re on different channel numbers?

Explanation: This illustrates a critical coexistence challenge in the 2.4 GHz ISM band where different technologies have different channel bandwidths.

Channel bandwidth comparison:

Wi-Fi (802.11b/g/n): - Typical channel widths are 20/22 MHz in 2.4 GHz (and can be wider if configured) - Channel 3 centers at 2.422 GHz - Spans from 2.411 GHz to 2.433 GHz

Zigbee (802.15.4): - 16 channels numbered 11-26 in 2.4 GHz band - Each channel occupies only 2 MHz bandwidth - Channel 15 centers at 2.425 GHz - Spans from 2.424 GHz to 2.426 GHz

Overlap calculation: - Wi-Fi channel 3: 2.411-2.433 GHz - Zigbee channel 15: 2.424-2.426 GHz - Complete overlap! Zigbee ch15 falls entirely within Wi-Fi ch3 bandwidth

Interference mechanism: 1. Wi-Fi occupies a much wider channel and often transmits at higher EIRP than 802.15.4 devices 2. When channels overlap, Wi-Fi energy can raise the noise floor for Zigbee/Thread receivers 3. Zigbee/Thread frames collide or require retries, reducing throughput and increasing latency

Coexistence strategies:

Option 1: Plan channels intentionally - Keep Wi-Fi on a non-overlapping plan (often 1/6/11 in 2.4 GHz) and avoid channels like 3 that overlap both neighbors - If Zigbee must stay on channel 15, prefer Wi-Fi channel 1 or 11 (and reduce AP transmit power where possible) - If Wi-Fi channel is fixed, consider moving Zigbee to channel 25 (or 20) based on an energy scan

Option 2: Migrate to 5 GHz - Move Wi-Fi to 5 GHz band - Leave 2.4 GHz for Zigbee, Bluetooth, Thread - 5 GHz/6 GHz provide many more non-overlapping channels than 2.4 GHz

Option 3: Use channel agility (when supported) - Periodically energy-scan and set the 802.15.4 channel during commissioning/maintenance - In industrial networks, 802.15.4 TSCH and Bluetooth LE use channel hopping to improve resilience in interference

Real-world note: Heavy Wi-Fi traffic on overlapping 2.4 GHz channels can cause significant packet loss and latency for 802.15.4 devices. Moving Wi-Fi to 5 GHz and tightening channel planning usually resolves it.

Question 11: An agricultural IoT system needs to monitor soil moisture across a 2 km^2 farm. Sensors are battery-powered and must last 10 years, transmitting 10 readings per day. Which combination of frequency band and protocol is most suitable?

Explanation: This workload is very low data rate (10 readings/day) but needs multi-kilometer coverage and decade-scale battery life. Among the options, a sub-GHz LPWAN such as LoRaWAN is the best match because it provides high link budget and is designed for infrequent uplinks with long sleep intervals.

Why LoRaWAN fits: - Sub-GHz propagation is generally more forgiving over long distances and through vegetation than 2.4/5 GHz - Long sleep intervals are practical when you only transmit a few times per day - The network architecture is designed for sparse sensors and gateway-based collection

Why other options are weaker here: - 5 GHz Wi-Fi: higher path loss and typically higher power/association overhead; usually assumes powered infrastructure - 2.4 GHz Zigbee mesh: end devices can be low power, but a farm-scale mesh typically needs powered routers and careful planning - BLE long range: can reach farther than “classic” BLE, but it is not a natural fit for wide-area, sparse sensors without significant infrastructure

Note: In some deployments, licensed LPWAN (e.g., NB-IoT) can also be a strong fit if coverage and subscriptions are acceptable; this question’s best answer is LoRaWAN among the listed options.

823.4 Quiz 2: Optional Practice Questions

Question: A smart home system needs to stream video from security cameras while also controlling low-bandwidth sensors. The home has thick concrete walls. Which frequency band strategy is most appropriate?

Explanation: A hybrid plan leverages strengths: 5 GHz provides higher bandwidth for video (often with multiple APs), while 2.4 GHz offers better penetration/range for distributed low-rate sensors (Zigbee/Thread/Wi-Fi IoT).

Question: At 100 meters, approximately how much less free-space path loss does 868 MHz have compared to 2.4 GHz?

Explanation: Using FSPL with d=0.1 km: FSPL_868 is approximately 71.2 dB and FSPL_2400 is approximately 80.0 dB, so the difference is approximately 8.8 dB (approximately 9 dB). This is why sub-GHz often has a sizable link-budget advantage at the same distance.

Question: An IoT startup wants a city-wide environmental sensor network. What’s the key trade-off between LoRaWAN (unlicensed ISM) and NB-IoT (licensed cellular)?

Explanation: Unlicensed spectrum is shared (cheaper per device but interference/duty-cycle constraints), while licensed cellular spectrum is managed by operators (better QoS/coverage but recurring subscriptions and less control).

823.5 Cellular IoT Technologies Comparison

After completing the quiz, review this comparison of cellular IoT options:

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graph TB
    subgraph "NB-IoT"
        NB1["Data Rate:<br/>250 kbps"]
        NB2["Mobility:<br/>Stationary/Low"]
        NB3["Coverage:<br/>+20 dB deep indoor"]
        NB4["Battery:<br/>10+ years"]
        NB5["Use Case:<br/>Smart meters, sensors"]
        NB6["Cost: $"]
    end

    subgraph "LTE-M (Cat-M1)"
        LM1["Data Rate:<br/>1 Mbps"]
        LM2["Mobility:<br/>Full handover"]
        LM3["Coverage:<br/>+15 dB"]
        LM4["Battery:<br/>5-10 years"]
        LM5["Use Case:<br/>Asset tracking, wearables"]
        LM6["Voice:<br/>VoLTE"]
        LM7["Cost: $$"]
    end

    subgraph "5G (mMTC / NR profiles)"
        FG1["Data Rate:<br/>kbps-Mbps (profile-dependent)"]
        FG2["Density:<br/>High device density"]
        FG3["QoS:<br/>Slicing / profiles"]
        FG4["Power:<br/>PSM/eDRX (device-dependent)"]
        FG5["Use Case:<br/>Smart cities, industrial sensing"]
        FG6["Latency:<br/>Profile-dependent"]
        FG7["Cost: $$$"]
    end

    COMP["Comparison:<br/>NB-IoT: Deep coverage, lowest throughput/cost<br/>LTE-M: Mobility + higher throughput<br/>5G: Adds capacity + slicing; IoT profiles vary<br/>All: Licensed cellular spectrum"]

    NB1 & NB2 & NB3 & NB4 & NB5 & NB6 --> COMP
    LM1 & LM2 & LM3 & LM4 & LM5 & LM6 & LM7 --> COMP
    FG1 & FG2 & FG3 & FG4 & FG5 & FG6 & FG7 --> COMP

    style NB1 fill:#2C3E50,stroke:#16A085,color:#fff
    style NB2 fill:#2C3E50,stroke:#16A085,color:#fff
    style NB3 fill:#2C3E50,stroke:#16A085,color:#fff
    style NB4 fill:#2C3E50,stroke:#16A085,color:#fff
    style NB5 fill:#2C3E50,stroke:#16A085,color:#fff
    style NB6 fill:#2C3E50,stroke:#16A085,color:#fff
    style LM1 fill:#16A085,stroke:#2C3E50,color:#fff
    style LM2 fill:#16A085,stroke:#2C3E50,color:#fff
    style LM3 fill:#16A085,stroke:#2C3E50,color:#fff
    style LM4 fill:#16A085,stroke:#2C3E50,color:#fff
    style LM5 fill:#16A085,stroke:#2C3E50,color:#fff
    style LM6 fill:#E67E22,stroke:#2C3E50,color:#fff
    style LM7 fill:#16A085,stroke:#2C3E50,color:#fff
    style FG1 fill:#E67E22,stroke:#2C3E50,color:#fff
    style FG2 fill:#E67E22,stroke:#2C3E50,color:#fff
    style FG3 fill:#E67E22,stroke:#2C3E50,color:#fff
    style FG4 fill:#E67E22,stroke:#2C3E50,color:#fff
    style FG5 fill:#E67E22,stroke:#2C3E50,color:#fff
    style FG6 fill:#E67E22,stroke:#2C3E50,color:#fff
    style FG7 fill:#E67E22,stroke:#2C3E50,color:#fff
    style COMP fill:#ecf0f1,stroke:#7F8C8D,color:#2C3E50

Figure 823.1

Cellular IoT Technologies: - NB-IoT: Best for stationary sensors with deep indoor penetration needs - LTE-M: Optimal for mobile applications requiring voice support and handover - 5G (NR profiles): Emerging options (e.g., RedCap) and slicing/capacity features; many massive-IoT deployments still use LTE-M/NB-IoT today

823.7 Summary

This comprehensive quiz chapter tested advanced understanding of wireless communication for IoT:

Key Topics Covered: - Electromagnetic properties: Frequency, wavelength, and propagation characteristics - Path loss calculations: FSPL formula and practical indoor/outdoor applications - Spectrum trade-offs: Licensed vs unlicensed, duty cycle constraints, regional regulations - Channel selection: Avoiding overlap, coexistence strategies, interference mitigation - Technology selection: Matching requirements to LoRaWAN, NB-IoT, LTE-M, Wi-Fi, Zigbee

Core Principles: - Smart agriculture deployments often use sub-GHz LPWAN for long battery life and multi-kilometer coverage - 2.4 GHz channel planning must account for Wi-Fi/802.15.4 coexistence - Regional spectrum regulations vary by geography with differing power and duty-cycle constraints - Link budget analysis determines viability by accounting for transmit power, path loss, and fade margins - Practical deployment scenarios require balancing range, data rate, power consumption, cost, and regulatory compliance

823.8 Further Reading

Books: - “Wireless Communications: Principles and Practice” by Theodore S. Rappaport - “RF and Microwave Wireless Systems” by Kai Chang

Standards: - FCC Part 15: Radio Frequency Devices (US regulations) - ETSI EN 300 220: Short Range Devices (European regulations) - ITU Radio Regulations: International spectrum allocation

Online Resources: - RF Wireless World: Frequency band tutorials - Electronics Notes: Comprehensive wireless technology guides - National Instruments: RF fundamentals

823.9 What’s Next

Having completed this comprehensive review, proceed to protocol-specific topics:

  • Wi-Fi for IoT: IEEE 802.11 standards, Wi-Fi 6/6E features, power save modes
  • Bluetooth and BLE: Classic Bluetooth vs BLE, connection modes, GATT profiles
  • Zigbee and Thread: IEEE 802.15.4 mesh networking, routing protocols
  • LoRaWAN: Long-range wide-area networks, spreading factors
  • Cellular IoT: NB-IoT, LTE-M, and 5G IoT capabilities