The solution instead seems to be multifaceted, including more spectrally efficient technologies, such as LTE and WiMax, as well as the introduction of additional pico- and femtocell base stations. These emerging approaches will be combined with existing techniques including network optimization, wifi offload, and the addition of more spectrum and more cell towers.
Traffic loads on cellular networks are growing at a faster pace than technology can accommodate. The latest Cisco Visual Networking Index estimates that mobile data traffic grew by a factor of 2.6 during 2010, and the index forecasts a 26-fold increase over the next five years (Figure 1), most of it driven by video and other real-time traffic. While LTE, WiMAX, and HSPA+ are more spectrally efficient than 3G technologies, the performance gains are not even close to meet the expected data traffic demand over the next few years.
To date, mobile operators have tried to contain the problem of congestion mostly with Wi-Fi off-load to relieve high stress points in their network and with the introduction of traffic caps that limit traffic from the heaviest users. Wi-Fi off-load has worked well for many operators, but Wi-Fi spectrum is limited and Wi-Fi is heavily used for other applications as well. As a result, its role in addressing the capacity crunch in the long term is necessarily restricted, especially since it uses license-exempt spectrum that everybody is entitled to use.
So far there is little evidence that traffic caps have reduced the impact of network congestion, or, for that matter, of traffic levels. In a recent report available here, I argue that traffic caps fail to specifically target traffic levels at peak hours (and, in fact, may encourage more usage at peak hours, with subscribers trying to save bandwidth on activities at off-peak hours, which are often considered less urgent or valuable). This is a real limitation in the efficacy of traffic caps because traffic during off-peak hours is essentially free to operators. It is only peak hour traffic that really matters-and that is responsible for congestion. The results (Figure 4) indicate the need for mobile operators to adopt a multi-pronged strategy that includes the adoption of different solutions to address specific traffic growth drivers. Perhaps even more importantly is the need to integrate those tools across their networks-and across their internal teams that are accustomed to work largely independent from each other.