Suggested Hardware¶

This information is correct as of March 15th

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Introduction¶

This document aims to provide users with an overview of the suggested PC and SDR hardware combinations that can be used to best explore the functionality of srsRAN. There are 100’s of possible combinations of PC, notebook, single board computer and SDR hardware that can demonstrate the uses of srsRAN. This list aims to provide three possible hardware packages that can help to guide users when choosing what to buy. These packages are grouped by price, with full set-ups cotsing >$400, >$3,000 and finally >$16,000. The three packages proposed here should provide any user with enough information to create their ideal set-up, which easily meets their needs.

Choosing Hardware¶

When choosing these packages we compared each hardware option under the same metrics. With one set for the computational hardware, and one for the SDR.

Compute Criteria¶

The following are the main specifications taken into account when selecting the compute platform for each of these packages:

• Cost - Overall cost of the machine

• Number of cores - This will affect overall performance

• Processor frequency - CPUs running at lower frequencies may struggle under heavy computational loads

• Cache size - A good indication of speed. More cache memory means certain computations will be faster.

• Number of threads - More threads will enable a processor to execute processes faster.

This is not an exhaustive list of criteria to look at when selecting a compute platform for SDR experimentation and development. Intended use-case will dictate choice the most here, as well as other external factors which can be subjective to either the user or overall use conditions.

Other useful things to take into account when choosing a compute platform for SDR research and experimentation are:

• Processor Cinebench score - This gives a good indication of a processor’s ability to deal with high computational load. Find out more here.

• Cooling ability - More cooling ability will ensure CPU performance does not drop off significantly under heavy load

• Portability - Some use-cases may benefit from a PC that is portable

SDR Criteria¶

When selecting the SDR options to highlight we took the following into account:

• Cost - Cost per unit of the SDR

• Driver - Which driver the SDR uses (Soapy, UHD, etc)

• Frequency range - The frequency range(s) the SDR operates in

• Bandwidth - Maximum possible bandwidth available

• Clock - Clock rate

• Channels - The number of channels available (SISO, MIMO, etc)

• FPGA - The specifications of the onboard FPGA

Much like when choosing compute hardware, the metrics you may look at when choosing an SDR will vary depending on use-case and other factors. This list is in no way exhaustive, but provides a good platform by which to compare options.

Package Overview¶

Each package will contain a recommended SDR and compute hardware bundle. With some appropriate use-cases for each. A full end-to-end system will require at least two SDRs and two Compute platforms. As previously mentioned, these packages represent possible combinations, and are by no means a gold standard of the types of hardware needed for SDR experimentation.

Package 1¶

SDR

PC

This package is inspired by our R. pi4 app note.

Such a set-up would allow users to create a cheap end-to-end network, for under $400 without the need for a main PC. To run a full end-to-end system using the above equipment a user would need 3 Raspberry Pi4 units and 2 LimeSDR minis. A Pi4 is needed for the EPC, eNB and UE, and a front-end is needed for both the eNB and UE. Due to the small size and portability of the system this setup is ideal for on-the-fly demos and testing of networks and applications that don’t require high-powered compute hardware or frontends.

Advantages¶

• Low cost

• Highly portable

Limitations¶

• Limited cell bandwidth (currently 5 MHz)

• Limited max bitrate in the UL

Package 2¶

SDR

PC

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This offers a step up from the previous package; in price and performance. The BladeRF micro 2.0 xA4 offers users a 2X2 MIMO configuration, higher max bandwidth, a larger frequency range, and a larger FPGA. The HP Omen 15 is a gaming notebook, meaning it is built for high performance and high CPU load for a sustained period of time. The intel i5 H is the main draw here, having scored highly in the cinebench r20 benchmarking test. This set-up is considerably more expensive and would cost roughly $ for a full set up of 2 PCs and 2 frontends.

Advantages¶

• Easily portable, with improved performance

• Suits nearly any use-case

Limitations¶

• Single cell configuration but up to 20 MHz 2x2 MIMO

• Non-expandable Bandwidth and operating frequencies

Package 3¶

SDR

PC

This system offers users the most potential in terms of RF-frontend capabilities on PC performance. The Ettus x310 offers users the largest frequency range, from DC to 6 GHz with the use of the appropriate daughter cards, a potential bandwidth of 160 MHz (requires the correct daughter cards), a multi-cell configuration and a powerful Kintex7 FPGA. The workstation offers an intel i7- which is capable of high intensity computations without a significant drop off in performance over sustained periods of time. The workstation offers 10 Gbps ethernet connection, which allows users full utilization of the 10 Gbps connection available on the x310. A full E2E system would cost a total of roughly $.

Advantages¶

• Carrier Aggregation

• Multi-cell configuration

Limitations¶

• Not all PCs will be able to interface via 10Gb ethernet. May have to use adapters.

Introduction to SDRs in Test and Measurement

Software-Defined Radios (SDRs) have revolutionized the field of test and measurement by offering unparalleled flexibility, adaptability, and cost-effectiveness compared to traditional test equipment. SDRs are versatile devices that use software to define their functionality, enabling them to perform a wide range of tasks in test and measurement applications. They can transmit and receive signals, generate and analyze waveforms, and adapt to various wireless communication standards.

SDRs provide the advantage of flexibility, as they can be easily reprogrammed to support different modulation schemes, frequency bands, and measurement techniques. This flexibility allows engineers to use a single device for multiple purposes, eliminating the need for specialized hardware for each specific test or measurement scenario. Moreover, SDRs can adapt to changing standards and evolving technologies through software updates, making them future-proof investments.

Calibration and Accuracy

One of the key challenges in using SDRs for test and measurement is ensuring accurate calibration. Calibration is crucial for reliable and precise measurements, as it compensates for imperfections and variations in the SDR hardware. Gain and phase calibration techniques are employed to compensate for variations in the signal amplitude and phase response. Frequency accuracy calibration addresses the need for precise frequency measurements, especially in applications such as spectrum monitoring and interference analysis. Linearity calibration ensures accurate measurements across the dynamic range of the SDR.

To overcome calibration challenges, manufacturers provide calibration routines and tools specifically designed for their SDR platforms. These routines typically involve using reference signals and known measurement standards to establish calibration coefficients that can be applied to the acquired data. Additionally, periodic recalibration and verification procedures are recommended to maintain measurement accuracy over time.

Signal Generation and Simulation

Generating and simulating complex signals is another challenge in test and measurement applications. SDRs need to provide signal fidelity, dynamic range, and modulation capabilities to accurately emulate real-world signals. Signal fidelity refers to the ability of the SDR to reproduce signals without introducing distortions or impairments. Dynamic range is crucial for accurately representing the range of signal amplitudes encountered in practical scenarios. Modulation capabilities allow the generation of signals conforming to various communication standards.

To tackle these challenges, SDRs employ advanced digital signal processing techniques and algorithms. These algorithms compensate for impairments such as distortion, noise, and non-linearities, resulting in more accurate signal generation. SDR platforms often provide comprehensive libraries and tools that facilitate the generation of complex signals by allowing users to define modulation schemes, signal parameters, and modulation sequences.

Signal Analysis and Measurements

Analyzing and measuring signals using SDRs come with their own set of challenges. The noise floor, signal-to-noise ratio (SNR), spurious signals, and distortion all impact measurement accuracy. Noise floor refers to the inherent noise present in the SDR system, which can limit the detection and measurement of low-level signals. SNR represents the ratio of the desired signal power to the noise power, indicating the quality of the measured signal. Spurious signals and distortion can arise due to imperfections in the SDR hardware or digital signal processing algorithms, affecting measurement accuracy.

To address these challenges, signal demodulation, decoding, and analysis algorithms are implemented in SDR software. These algorithms extract the desired signals from noise and mitigate distortions, enabling accurate measurements. Various measurement techniques, such as power, frequency, and phase measurements, are employed to quantify signal characteristics. Additionally, advanced algorithms for noise reduction, interference rejection, and error correction are utilized to improve the accuracy of measurements.

Bandwidth and Sampling Rate

Handling high bandwidth and sampling rate requirements is a significant challenge in test and measurement applications, particularly when dealing with wideband signals or high-frequency components. Lower cost SDR hardware typically has limitations on available bandwidth and sampling rate, which can constrain the measurements, however, the highest performing SDRs offer 1 GHz and 3 GHz sampling bandwidths per radio chain with up to 16 radio chains available. These higher bandwidth and sampling rate capabilities are crucial for capturing and analyzing signals with fine time and frequency resolution.

To address this, high performance SDRs utilize parallelization techniques to process signals in parallel across multiple radio chains and further can be synchronized across multiple SDR devices. By combining the inputs and outputs of multiple independent radio chains and through the use of high-performance analog-to-digital converters (ADCs) and digital-to-analog converters (DACs), higher bandwidth and sampling rates can be achieved. Additionally, sophisticated signal processing algorithms, such as polyphase filter banks , can be utilized to effectively utilize the available hardware resources and optimize signal capture and analysis.

Synchronization and Timing

In multi-channel and multi-device SDR test and measurement setups, achieving synchronization and accurate timing is vital for precise measurements. Synchronization errors can introduce phase offsets, timing misalignment, and inter-channel interference, leading to measurement inaccuracies. In applications such as beamforming, MIMO (Multiple-Input Multiple-Output) systems, or distributed sensing networks, synchronization becomes even more critical.

To address synchronization challenges, various techniques are employed, such as offering clock inputs, triggers, and pulse-per-second (PPS) ports. Through the use of these techniques, synchronization utilizes external clocks and triggers to synchronize the clocks of multiple SDR devices, ensuring accurate timing alignment. Distributed clocking systems provide a centralized clock source that is distributed to multiple devices, enabling synchronized operation. Hardware triggers allow precise triggering and synchronization between different SDR devices, ensuring simultaneous measurements.

Software Development and Integration

Developing and integrating software for SDR-based test and measurement applications can be a complex task. Engineers need to consider factors such as programming languages, software frameworks, and compatibility with existing measurement systems. Choosing the right programming language and software framework is crucial for efficient and maintainable development. 

To address these challenges, manufacturers provide comprehensive software development kits (SDKs) and application programming interfaces (APIs) that simplify the development process, along with the ability to work out of the box with common software tool kits, such as GNU Radio. These tools offer libraries, examples, and documentation to facilitate software integration and customization.

Future Trends and Solutions

The future of SDRs in test and measurement holds exciting possibilities. As wireless communication technologies evolve, the need for SDRs with very high bandwidths and multiple independent radio chains becomes increasingly critical. Advancements in SDR hardware, including higher channel counts with faster ADCs and DACs, coupled with wider frequency coverage, will enable higher bandwidth and sampling rate capabilities. Furthermore, improvements in signal processing algorithms, such as machine learning-based approaches, will enhance signal analysis and measurement accuracy.

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