5G Electric Fields Strength With Software Defined Radios

2022 · Unclear · Insufficient evidence

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UnclearInsufficient evidencePaper 641

Study snapshot

Publicationmanual · 2022

Study typeexposure_assessment

Reported directionUnclear

Evidence ratingInsufficient

Abstract

5G Electric Fields Strength With Software Defined Radios Minucci F. et al. 5G Electric Fields Strength With Software Defined Radios. IEEE Open Journal of the Communications Society, 2022, doi: 10.1109/OJCOMS.2022.3222537. Abstract The effect of electromagnetic radiation on public health is a recurring topic in the societal and political discourse, peaking with the introduction of every new generation of cellular technology. With the introduction of 5G, promising high peak download speeds as well as high-power beams, there is a need to revisit traditional measurement approaches. ICNIRP, a.k.a the International Committee on Non-Ionising Radiation Protection, offers a useful guideline to evaluate the electromagnetic field exposure of living tissues and provides some limits to keep exposure well below the threshold where it is considered harmful. However, modern packet radio technologies such as 5G or Wi-Fi are different from old broadcasting technologies. They deliver high power in very short bursts, spread over a wide band, thus increasing the difficulty of measuring electric fields with traditional instruments, such as spectrum analyzers. In addition, 5G promises a high spatial focusing performance, which means that the field can vary significantly even in a small area. Hence, measurements with a higher spatial density than we can achieve with expensive and bulky spectrum analyzers are urgently needed. Software-defined radios (SDRs), as a size-and cost-efficient alternative, can be used to capture signals in the time domain and thus increase measurement accuracy. However, software-defined radios are not designed to be used as RF power meters. They require accurate calibration and data analysis to ensure the measured power is correct. The aim of this work is to provide a general framework to calibrate SDRs, enabling them to measure RF power and extract the corresponding electric field value. Subsequently, the influence of the SDR parameters on the accuracy of the electric field measurement is investigated. To assess the performance of the proposed calibration framework in a real-life scenario, we rely on our private 5G network with a calibrated SDR to measure the RF power from a 5G network. Our measurements show that the average electric field exposure of 5G networks is well below 1 V/m. Excerpt The electric field calculation based on our 5G measurements is presented in Table 3. As expected, the electric field is stronger in positions 1 and 6 from Fig. 10, which are next to the UE. In all other positions, the electric fields are considerably lower. The average electric field values are never above 0.6 V/m. However, the electric field for a single transmission from the UE can peak at 40.82 V/m when measured with a near-field probe. Peaks from the base station, on the other hand, never surpassed 2.084 V/m. Measurements performed with two devices do not show any significant change in the electric field value generated by the base station, which is the focus of this research work. One important outcome of this measurement is that, while the regulator is focused on limiting the power of downlink transmission, the greatest contribution to RF exposure on people comes from the UE itself, similarly to what was found in [37]. Another important aspect to consider is that our results are in line with what was measured in [29]. This means that a low-cost SDR based system can be effectively employed for this kind of measurement. ieeexplore-ieee- org.libproxy.berkeley.edu/stamp/stamp.jsp?tp=&arnumber=9955380&isnumber=8901158

Machine Enhanced Logic

AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeexposure_assessment

Effect directionunclear

PopulationNot supplied

Sample sizeNot supplied

ExposureRF

Evidence strengthInsufficientConfidence: 78% · Peer reviewed: yes

Main findings

The paper proposes and evaluates a calibration framework to use software-defined radios (SDRs) to measure RF power and derive electric field strength in a private 5G network. Reported measurements indicate average electric field exposure values below 1 V/m (average values never above 0.6 V/m), with peaks for a single UE transmission up to 40.82 V/m (near-field probe) and base-station peaks not surpassing 2.084 V/m.

Outcomes measured

Electric field strength (V/m)
RF power measurement accuracy (via SDR calibration)

Limitations

Frequency band/center frequency not stated in the provided abstract/excerpt
Measurement setting described as a private 5G network; generalizability to other deployments not stated
Sample size/number of measurement locations and protocol details not fully provided in the abstract/excerpt
Health outcomes are not assessed; results are exposure/measurement-focused

View raw extracted JSON

{
  "study_type": "exposure_assessment",
  "exposure": {
    "band": "RF",
    "source": "5G network (base station and user equipment) measured with software-defined radio",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": null
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "Electric field strength (V/m)",
    "RF power measurement accuracy (via SDR calibration)"
  ],
  "main_findings": "The paper proposes and evaluates a calibration framework to use software-defined radios (SDRs) to measure RF power and derive electric field strength in a private 5G network. Reported measurements indicate average electric field exposure values below 1 V/m (average values never above 0.6 V/m), with peaks for a single UE transmission up to 40.82 V/m (near-field probe) and base-station peaks not surpassing 2.084 V/m.",
  "effect_direction": "unclear",
  "limitations": [
    "Frequency band/center frequency not stated in the provided abstract/excerpt",
    "Measurement setting described as a private 5G network; generalizability to other deployments not stated",
    "Sample size/number of measurement locations and protocol details not fully provided in the abstract/excerpt",
    "Health outcomes are not assessed; results are exposure/measurement-focused"
  ],
  "evidence_strength": "insufficient",
  "confidence": 0.78,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "5G",
    "electric field strength",
    "RF exposure",
    "software-defined radio",
    "SDR calibration",
    "measurement framework",
    "base station",
    "user equipment",
    "near-field probe",
    "ICNIRP"
  ],
  "suggested_hubs": [
    {
      "slug": "who-icnirp",
      "weight": 0.6,
      "reason": "ICNIRP guidelines/limits are discussed as the exposure evaluation framework."
    },
    {
      "slug": "5g-policy",
      "weight": 0.55,
      "reason": "Focuses on 5G exposure measurement and implications for assessing compliance/exposure in 5G contexts."
    }
  ]
}

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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1109/ojcoms.2022.3222537
PubMed: Not supplied

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