Finally, optimization solutions must account for the type of device a subscriber is using and the type of content he or she is requesting. By being aware of the device type and the content that’s being requested, operators can send only the bandwidth that’s necessary for both, reducing what’s required to send “the best video in this particular context” as opposed to “the best video.”

Systematically confronting matters of video optimization empowers operators to get the most out of their LTE optimization efforts and emphasizes that an operator has a flexible platform, one that enables dynamic application of optimization practices and best suits the ever-changing needs of the operator’s network—a quick fix for network problems as they arise won’t cut it. This type of platform ultimately leads to reduced network traffic during peak hours as well as improved customer QoE.

Tackling congested flows and congestion hotspots

Optimizing all video traffic at all times is unnecessary, not to mention it’s expensive, since all-inclusive video optimization is a CPU-intensive function. Congestion-aware optimization that occurs automatically when networks reach certain congestion thresholds can potentially reduce video stuttering and stalling, improving mobile-video delivery without the need for a huge server farm.

Applying just the right amount of optimization to congestion hotspots exactly when it’s needed, based on current network conditions, device capabilities, characteristics of the mobile content, operator policies, and customer price plans, leads to CAPEX (capital expenditures) savings and enhances customer QoE. The rest of the network is allowed to operate normally, which significantly reduces the cost of deploying optimization solutions and presents the best possible QoE to customers at all times.

Video optimization solutions can also provide LTE network operators with an objective measure of the video quality on their networks, allowing them to compare the original against the optimized version. When operators can compare the difference in video quality between optimized traffic and non-optimized traffic, they can draw more intelligent conclusions about their networks’ capabilities. With a better grasp of network traffic behavior, they can then take advantage of additional revenue opportunities, such as service offerings tailored to heavy video users that can be made available because of the increase in mobile-data traffic.

Congestion-aware optimization refers to more than just the amount of LTE network traffic in any given instance—it refers to the type of video content, the devices in use and the ways in which optimization occurs. Optimization benefits two sides of the wireless-network spectrum of operations: the operators themselves and their subscribers. It allows the operators to minimize the costs associated with network and infrastructure upgrades yet still deliver high-quality services to their subscribers, who are demanding more and more mobile-video data. In an already crowded LTE economy, congestion-aware mobile-video optimization provides operators with an effective plan of action for monitoring and utilizing their network resources while maintaining subscriber satisfaction and profitability.

Leveraging optimization to truly harness the power of 4G LTE networks

A 4G LTE network has many benefits that a legacy network does not. Some network architects believe there’s no immediate need to optimize LTE networks, or that they can cover all their bases with new network technologies, such as self-organizing network (SON) solutions. But that’s a misconception, because the rate of growth of mobile traffic on an LTE network typically outpaces the increase in available bandwidth on the network, which is why a robust optimization solution is still critical in helping operators improve QoE while saving large amounts of CAPEX and OPEX (operating expenditures) by delaying the need for additional network investments.

For example, messaging and voice revenues are beginning to stagnate, positioning data as not only the primary source for operator revenues but also for expenses, since those operators will subsequently need to evolve their data services. Even a well-provisioned network requires optimization, and any operator’s long-term strategy should include the prevention of data bottlenecks.

Just like 3G, LTE is radio based, so regardless of how much increased bandwidth it provides, the total amount of bandwidth is still finite. Network congestion will continue to be an issue because subscribers will continue to vie for limited network resources during peak hours, making optimization necessary if this problem is to be tackled head-on. Subscribers also expect all services on LTE networks to be superior to the ones on legacy networks; a dynamic optimization solution is an essential insurance policy against subscriber churn, because network hiccups, no matter how minor, will be noticed, and have the potential to drive subscribers to competing operators.

In today’s data-centric and unforgiving consumer economy, operators can’t afford to jeopardize quality of experience on their way to reducing data-consumption and infrastructure expenses. QoE is the utmost priority in LTE networks, where quality is expected, not just demanded. LTE network-optimization solutions are imperative to ensure that neither operators nor their subscribers have to compromise.