Spectral efficiency is a term that often comes up when people talk about radio communications. Understanding it is helpful when comparing two wireless systems. You could be comparing two systems that both use 80 MHz of spectrum, for example, but the amount of usable data each can send could be wildly different. One reason for the difference can be because individual technologies do things in more or less efficient ways compared to each other.
Spectral efficiency refers to the amount of data that can be transmitted over a specific bandwidth. You can use it to compare how efficiently two different systems utilize the same frequency. This is important when you consider the fact that spectrum is typically constrained — there’s only so much frequency available for transmission, so using it in a way that maximizes the capacity or amount of throughput available can pay off in higher throughput. Spectral efficiency is typically referred to as bits per second per hertz (bps/Hz).
You calculate spectral efficiency with a simple formula:
Spectral efficiency = (Capacity in bps) / (bandwidth in KHz)
As an example, the Tarana G1 computation for a single sector (Base Node) would look like this:
30 bps/Hz = (2400 Gbps) / (80 MHz)
A spectral efficiency of 30 bps/Hz is considered a very high number and one of the many highlights of G1. Without high spectral efficiency, even the most groundbreaking technology will be less useful.
Of course there are other options besides G1. As a counter example, let’s look at a Wi-Fi system. In our example, we’ll use an 802.11ac 2×2:2 MIMO system. Using an 80 MHz-wide channel, the maximum PHY data rate is 867 Mbps.
10.8 bps/Hz = (867 Mbps) / (80 MHz)
What this means is G1 is approximately three times as efficient at transmitting data as Wi-Fi. When you are an operator making money off every unique bit of information transmitted, this is a real game changer.
One way to think about spectral efficiency is like automobiles. You might have two cars with identical engines but one is tuned significantly better than the other. Horsepower can be used to distinguish between the slower (lower horsepower) car and the faster one. Spectral efficiency can be thought of in a similar fashion. Any communications technology can transfer information, but some technologies do it much better and faster.
This is why spectral efficiency is such an important criteria for measuring wireless radio performance. Every duplicate transmission or slower data rate can impact overall subscriber experience, throughput, and speeds. Applications like online gaming or video conferencing, in particular, are especially susceptible to retransmissions that can cause unacceptable delays and jitter in the applications.
Another reason spectral efficiency can fluctuate across different solutions is interference. Interference garbles transmissions which, in turn, means the same data has to be transmitted again. Depending on how much interference there is the same data could be retransmitted again and again before finally getting delivered successfully. This decreases the overall capacity of a link because more time is spent transmitting less data.
G1 achieves such impressive spectral efficiency due to how it handles multiple parameters that can degrade performance like interference. Technologies that we’ve written about before, like asynchronous burst interference cancellation (ABIC) are designed to remove interference even during payload transmission. This ensures a clean, clear signal with low latency and jitter and a great subscriber experience.