Massive MIMO (massive multiple-input multiple-output) is a type of wireless communications technology in which base stations are equipped with a very large number of antenna elements to improve spectral and energy efficiency.
The demand for wireless throughput, communication reliability, and user density will always increase. Massive MIMO technology is being developed for 5G wireless communication systems because many users can be served simultaneously with very high throughput. Processing techniques such as beamforming can concentrate the signal energy from massive MIMO antenna arrays to overcome the propagation losses inherent in high-frequency transmission in 5G systems.
How Is Massive MIMO Different?
Massive MIMO is an extension of multi-user MIMO or MU-MIMO, in which the base station transmitter simultaneously communicates with multiple mobile station receivers using the same time-frequency resources, improving the spectrum efficiency. MIMO implementation starts with a 2x2 channel antenna array. Massive MIMO systems typically have hundreds or even thousands of antenna channels in the array.
Challenges in Massive MIMO
Despite its advantages, massive MIMO has some limitations.
Power consumption. To meet the 5G standards and millimeter-wave range for the next generation of wireless communication systems, massive MIMO incorporates intelligent array design and makes use of spatial signal processing techniques, including beamforming. The need to have a dedicated transmit/receive module for each antenna element in such systems increases power consumption and system cost. Hybrid beamforming alleviates the power consumption issues of massive MIMO systems by partitioning the beamforming between digital and RF domains, and combining multiple array elements into subarray modules. It requires fewer transmit/receive modules, lowering the power consumption and system cost.
Channel reciprocity. Massive MIMO can work in both frequency division duplex (FDD) and time division duplex (TDD) transmission modes. In 5G, Massive MIMO performs best in TDD mode, where the channel estimation is based on channel reciprocity. Unlike FDD systems, where the uplink and downlink communications occur on separate frequency bands, the estimated channel in the uplink in TDD systems is equivalent to its downlink counterpart. Thus, it can be used for precoding in the downlink. However, in practical TDD systems, the transmit and receive RF chains at the base station differ with the user terminals. This violates the reciprocity and requires reciprocity calibration to overcome this problem.
- Design and synthesize complex antenna elements and massive MIMO phased arrays and subarrays
- Design and partition hybrid beamforming systems intelligently across digital and RF 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