5G is fast becoming a reality driving new use cases and business models across industries, from cognitive technologies and robotics to industrial IoT, telemedicine and self-driving vehicles. However, the telecoms industry is at a crossroads — it needs to accelerate the 5G rollout while reinventing itself technologically to manage the challenges along the way.
One of these key challenges is ensuring the performance of wireless cellular networks is up to the 5G standards, meaning the efficiency of spectrum frequencies needs to be maximized. The latest innovation in coherent beamforming can meet these requirements by marrying performance with cost-efficiency.
Re-inventing RAN design for 5G and beyond
So far, the air interface provided by the Radio Access Network (RAN) has been impacting wireless cellular networks by limiting their performance. 5G RAN is significantly more capable than 4G thanks to several factors, including the introduction of wider channels in the sub-6 GHz bands, a substantial increase in sub-6 GHz spectrum efficiency, the use of mmWave spectrum and expanded cloud orchestration capabilities.
In the traditional Frequency Range 1 (FR1) bands (hundreds of MHz to 6 GHz), channels as wide as 100MHz are now allowed in 5G leading to a fivefold increase in channel bandwidth compared to 4G. A wider channel enables a greater volume of information to flow, delivering higher download/upload speeds in the cellular network.
5G also adds FR2 to the traditional frequency range. FR2 enables significantly higher frequencies than FR1 (e.g., 15-70GHz). MmWave spectrum supports even wider channel bandwidths than FR1 — from hundreds of MHz to GHz — subsequently increasing the information flow rate. However, mmWave bands suffer from high propagation loss and even total link loss in non-line-of-sight transmissions. The transmission range in FR2 is so much smaller than in FR1 that using the same conventional RAN design, as in FR1, is not the right option in practice.
The challenges of phase-array beamforming
Phase-array beamforming can eliminate the range difficulty in mmWave systems by deploying numerous active antenna elements configured in a sizable dense array to transmit and receive wireless signals coherently (i.e., in an exact phase and magnitude mutual relationship). There’s a lot to learn from techniques leveraged for radars and space exploration. For instance, by controlling the phase and magnitude of the signals at every antenna element, we can create constructive and destructive electromagnetic interference patterns over the air, generating physical, 3D beams that act like spotlights.
Using physical beams in 5G mmWave communications means the large number of active antennas used can multiply signal strengths, extending the range accordingly. In addition, user separation occurs naturally, as beams illuminate only narrow solid angles. As a result, phased-array beamforming achieves spatial multiplexing (i.e., the transmission of multiple streams of data over the same bandwidth) easily. Spatial multiplexing is a powerful way to increase system capacity.
Ensuring all active antenna elements operate synchronously is fundamental to actually obtain these beneficial effects in practice. These antenna elements need to be calibrated to high precision under all conditions. However, this can prove a challenging design specification, especially when looking to drive cost-efficiencies.
Delivering RF coherency in Massive MIMO systems
We’ve already discussed that 5G significantly increases the FR1 spectrum efficiency (number of bits per Hz). Like mmWave systems, a general approach for achieving this goal is with Massive MIMO (MaMIMO) active antenna arrays, which have 16, 32, or 64 active antenna elements rather than 2, 4, or 8 as in 4G.
MaMIMO systems drive two general use cases. The first use case refers to time-division multiplexing (TDD) systems based on channel sounding and signal processing to obtain the beamforming effects of phased arrays. Channel sounding consists of transmitting overhead pilot signals to measure the channel characteristics, including the radio chains (baseband-to-baseband estimations). Using these channel measurements, an appropriate computation creates constructive and destructive interference patterns — just like in the case of phased arrays.
Since channel sounding and the computations are done for receive and transmit paths respectively, this method is appropriate for TDD where the two paths are identical (channel reciprocity). While signal boosting and range extension are achieved consistently in TDD systems, spatial multiplexing is more challenging due to practical errors in channel estimation and hardware impairments. Nevertheless, frequency-division multiplexing (FDD) systems using this method have shown inferior performance to date due to a lack of channel reciprocity.
The second MaMIMO system use case is based on phased-array physical beams and is appropriate for both TDD and FDD. Using physical beams increases the signal strength and range and allows for easy spatial multiplexing. However, MaMIMO’s performance relies on the quality of its implementation. Roughly synchronizing and calibrating the array achieves moderate range extension and little capacity increase. More significant range extension and capacity increases are only possible when the array elements are precisely synchronized and calibrated, such as within a few degrees in phase and a fraction of dB in magnitude error.
We have named this level of precision ‘RF Coherency’ because it produces results practically indistinguishable from ideal phased arrays (zero phase/magnitude errors).
Combining higher performance with cost-efficiencies
Recent field trials have demonstrated it is possible to achieve RF Coherency in 4G and 5G active arrays with reduced costs. New RF synchronization and calibration methodologies have rendered RF Coherency possible, implemented with low-complexity custom mixed-signal integrated circuits, printed circuit board connectivity methods, and software/firmware methods.
This RF Coherency technology applies to all MaMIMO systems (16-64 Tx/Rx), including low-cost MaMIMO arrays with reduced radio chains. In this case, each radio chain connects to the entire active aperture as opposed to conventional MaMIMO arrays, where each radio chain only connects to a small portion of the active aperture.
Advanced AI/ML techniques redefine spectral efficiency
Self Optimized Network (SON) technology, which is another name for Cloud orchestration in traditional RAN, has been mostly limited to simple configuration updates and occasional RF coverage redistribution with Remote Electrical Tilt antennas. The introduction of MaMIMO in 5G and RF Coherency pave the way for enhancing Cloud orchestration and improving network performance.
Cognitive technologies such as artificial intelligence and machine learning have a critical role in boosting spectral efficiency. For instance, cloud-based on closed-loop artificial intelligence and machine learning techniques can dynamically and automatically control the precise shape and placement of the 3D physical beams in the second MaMIMO use case outlined above. As a result, there is a drastic reduction in cell-to-cell interference and optimum RF energy to match user traffic demands, leading to a substantial capacity increase and improved user experience.
The Open RAN interfaces are a key driver for the ‘Super-SON’ capability. Open RAN and RF Coherency technologies open up new opportunities for carriers to leverage a highly advanced 5G RAN solution.
Driving innovation in the global telecoms industry
Improved spectral efficiency and beam agility using phase coherency and massive MIMO Open RAN technologies enable wireless networks to deliver the high performance 5G requires cost-efficiently. The innovation in coherent beamforming creates new opportunities across markets worldwide. These combined technologies enable various deployment models in very dense developing markets like India and LATAM, empowering more advanced economies to leverage new use cases requiring higher performance and precision applications.
These innovative technologies will be essential when looking beyond 5G to achieve the 6G key performance goals for enabling applications using ultra-dense deployment topologies and more demanding spectrum requirements.