This paper demonstrates how you can use MATLAB® and Simulink® features and toolboxes to:
- Design and synthesize complex antenna elements and MIMO phased arrays and subarrays
- Partition hybrid beamforming systems intelligently across RF and digital domains
- Validate spatial signal processing algorithm concepts
- Verify link-level designs using high-fidelity simulations
- Evaluate the impacts of failed or imperfect elements and subarrays
- Eliminate design problems before building hardware
A fundamental goal of MATLAB and Simulink products for this application is to provide a direct path to expand the level of fidelity of the model over the many phases of project development. This includes tasks such as bringing measured data into the model for the antenna pattern and the propagation paths. It also includes expanding the level of fidelity of the RF chain by bringing in models of RF components in the context of multidomain simulation with Simulink.
Note: In the examples below, we use Phased Array System Toolbox™, Antenna Toolbox™, RF Blockset, RF Toolbox™, Communications Toolbox™, and Global Optimization Toolbox to complete the associated workflows.
Challenges Designing Massive MIMO Arrays for 5G
As 5G standards continue to evolve, the goals for higher data rates, lower latency network access, and more energy efficient implementations are clear. Higher data rates drive the need for greater bandwidth systems. The available bandwidth in the spectrum up through 6 GHz is not sufficient to satisfy these requirements. This has moved the target operating frequency bands up into the millimeter wave range for the next generation of wireless communication systems.
Intelligent Array Design with Beamforming
Smaller wavelengths at these higher frequency bands enable implementations with more antenna elements per system within small form factors. Signal path and propagation challenges associated with operating at these frequencies also increases. For example, the attenuation due to gas absorption for a 60 GHz waveform is more than 10 dB/km, while a 700 MHz waveform experiences an attenuation on the order of 0.01 dB/km. You can offset these losses with intelligent array design and the use of spatial signal processing techniques, including beamforming. This type of processing is enabled by massive MIMO arrays and can be used directly to provide higher link-level gains to overcome path loss and undesirable interference sources.
To achieve the most control and flexibility with beamforming in an active array design, it is desirable to have independent weighting control over each antenna array element. This requires a transmit/receive (T/R) module dedicated to each element. For array sizes that are typical of a massive MIMO communication system, this type of architecture is difficult to build due to cost, space, and power limitations. For example, having a high-performance ADC and DAC for every channel (along with the supporting components) can drive the cost and power beyond allocated design budgets. Similarly, having variable gain amplifiers in the RF chain for each channel increases the system cost.
Hybrid beamforming is a technique you can use to partition beamforming between the digital and RF domains. System designers can implement hybrid beamforming to balance flexibility and cost tradeoffs while still fielding a system that meets the required performance parameters. Hybrid beamforming designs are developed by combining multiple array elements into subarray modules. A transmit/receive (T/R) module is dedicated to a subarray in the array and therefore fewer T/R modules are required in the system. The number of elements, and the positioning within each subarray, can be selected to ensure system-level performance is met across a range of steering angles.
Using the transmit signal chain as our first example, each element within a subarray can have a phase shift applied directly in the RF domain, while digital beamforming techniques based on complex weighting vectors can be applied on the signals that feed each subarray. Digital beamforming allows control of the signal for both amplitude and phase on signals aggregated at the subarray level. For cost and complexity reasons, the RF control is typically limited to applying phase shifts to each of the elements.
Systems such as the one shown in Figure 1 are complex to develop. You can use modeling techniques to design and evaluate massive MIMO arrays and the corresponding RF and digital architectures needed to help manage their complexity. With these techniques, you can reduce risk and validate design approaches at the earliest stages of a project. We will first look at an array design example.
We have selected parameters for each of the examples that are common in the 5G wireless community, but all of the examples shown can be modified to match your desired configuration.