5G air interfaces need channel measurements: Page 2 of 3

November 02, 2015 //By Sheri DeTomasi
5G air interfaces need channel measurements
Sheri DeTomasi lloks at why 5G air interfaces will need channel measurements to meet the upcoming technical challenges.
Signal generation and analysis

To meet the high demands for 5G, the air interface standards will likely include mmWave frequencies up to 100 GHz, with 500 MHz to 2 GHz bandwidth, and with multichannel support. That's a lot to consider. The requirements will place great demand on the channel sounding measurement system. The measurement system needs to support these core requirements and provide repeatable measurements. Key components for this measurement system will be a wideband DAC (Digital to Analog Converter) in the form of a baseband AWG (arbitrary waveform generator) and an ADC (analog-to-digital converter) that will take the form of a wideband digitizer or oscilloscope to support the needed bandwidth and provide enough resolution to support the dynamic range needed to capture the signal. Also, because 5G is not yet defined, the test equipment should be flexible so that it can be configured and reconfigured as the test requirements and standards evolve.

Data capture and storage

When you consider the raw data that needs to be collected with a wideband measurement system that also has multi-channel capability, an eight-channel, 1 GHz bandwidth measurement can consume gigabytes of data in just one second, quickly filling disk drives. In addition, consider how to get this data from the ADC to a storage device. It's nearly impossible for the data to be captured and streamed in real-time. Disk drive manufacturers might like this because they will sell more storage, but it's just not practical. Instead, there are two other data capture-methods to consider that can reduce the amount of collected data:

  • If the sounding signal is less than one transmitting period, you can capture only the effective data or only the data needed to perform the CIR calculations. This method can greatly reduce the data collection.
  • Taking this one step further, you can perform the wideband measurement with real-time autocorrelation and signal processing with an onboard FPGA to produce the effective CIR data within the measurement system, now only the CIR results need to be saved. Thus, significantly saving storage space and providing the CIR results much faster.

Channel parameter estimations

Much of the research to date has focused on a single channel. MIMO (multiple input, multiple output) channels, however, introduce spatial and correlation information. The key issue with MIMO channels is how to estimate the spatial parameters. This includes parameters such as AoA (angle of arrive), AoD (angle of departure), and AS (angular spread). There are several channel parameter estimation algorithms that can be considered including beamforming based, subspace based, and ML (Maximum Likelihood) based. For consistency, coherence, and estimation performance, the ML-based estimation algorithms provide the very good performance for MIMO channel parameter estimations. Specifically, the SAGE (space-alternating generalized expectation-maximization) algorithm (ML based) with relativity low computing, is widely accepted by the research community.

Next: Calibrate and synchronize

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