In wireless networking, the most precious resource is wireless (typically radio) spectrum. Therefore, when evaluating which wireless technology to use for a particular network, spectral efficiency – the measure of how efficiently a technology is able to use the available spectrum to send and receive data – is a key deciding factor.
Today, spectral efficiency is measured in terms of bits per second per Hertz, or b/s/Hz. This figure provides a useful comparison between technologies and deployment models, with a higher number offering more efficient use of the wireless spectrum. This makes a wireless network technology more attractive than its less-efficient cousins, as spectrum is a finite resource; the more efficient use that can be made of it, the better.
Although not exclusively, spectral efficiency is primarily the concern of wide-area wireless networks, such as the LTE networks operated by the major cellular carriers. These networks are subject to extreme scrutiny by their operators, who are keen to extract as much performance as possible and are acutely aware of the challenges of limited spectrum.
Consider a traditional macrocell deployment by a cellular network operator. Over the coverage area of the macrocell, the average spectral efficiency can be calculated fairly easily, accounting for the drop-offs in signal quality at the edges of the cell and those clients closer to the base station which are receiving a better than average signal.
The same applies to a point-to-point or point-to-multipoint wireless link or sector. In all 3 cases, the spectral efficiency calculation takes into account one link in the case of a point-to-point deployment, or one access point/base station and their associated clients in the other cases.
As more devices, primarily mobile devices but also an increasing proliferation of network-connected cameras and IoT devices connect to these networks and shift towards more sustained, higher data rate applications such as streaming video, efficiency of the wireless network becomes paramount. With finite spectrum, there is only so much capacity available from an inefficient technology that relies on wider and wider channel bandwidths to handle the increasing data load.
In 2020, spectral efficiency as calculated today for a single wireless link, sector or cell will not be as important as it is today due to the changing realities of application usage, user density and network technologies.
Instead, a new measurement will be used that properly reflects the increasing impact of network densification:
Bits per second per Hertz per square kilometre (b/s/Hz/km2) or, the network densification score.
This measurement provides a much more insightful and accurate figure for a wireless network operator over a given area, such as a dense urban zone. The spectral efficiency of individual sectors or cells becomes much less important when instead of one cell covering the whole area, 20 or 30 smaller ‘islands’ of high-speed connectivity exist within the original ‘sea’ of lower-speed coverage.
For the resulting figure to be meaningful, it would be most useful for the wireless network operator to only consider those networks which they operate, and calculate separate values for different types of network (cellular, WiFi, combined, etc.) As well as being useful for engineering and planning purposes, an especially good network densification score would make a useful marketing pitch as well.
Which technologies and deployment models contribute most significantly to increasing the network densification score? Certainly millimetre-wave technologies have tremendous potential, with their combination of physically small equipment size, high bandwidths, narrow beam widths and short ranges. Small cells in more traditional frequency bands such as 5 GHz also stand to contribute positively as well, as long as they are properly co-ordinated with one another during frequency planning.
Improving the spectral efficiency of single links, sectors or cells is also a possibility, though it is increasingly difficult to make meaningful improvements to the average spectral efficiency of a network or area by doing so. Typically, environmental obstructions, reflections, material penetration issues and other detriments to wireless network performance ensure that the number of clients able to reliably use higher-order modulations schemes such as 1024 QAM, or even in many cases 256 QAM, are limited.
When determining which wireless network to use, or which combination of technologies and deployment models to use to build a wireless network, the network densification score will play a key part in making the right decision. For the end user, the higher the better at that moment in time – for the network operator, how the score matches up against the investment required to reach it will be highly important to ensure as much as possible that the most efficient network is built – efficient in the sense of spectrum, money and time.
As for the importance of spectral efficiency as a whole, it will only increase as wireless networks continue to be the preferred and often only method of network connectivity for billions of people and devices across the world. The evolution from single static figure to network densification score will be important to make sure that the relative performance of networks, technologies and deployment models stays measurable and comparable.