One of the biggest challenges faced by network operators is a phenomenon known as Cell Edge Interference. This occurs where adjacent cell towers direct radio frequencies (RF) across their target areas, and those signals overlap with signals from other cell towers. At the cell edge, end user performance is significantly and negatively impacted. Moreover, because of the density of tower distribution in some areas, cell edge interference can impact up to 30 percent of total area covered by the cell towers in a cluster. This means users are experiencing reduced network performance in one-third of the area covered.
As troubling as Cell Edge Interference is in today’s networks, it is expected to become more critical as network operators deploy more cell sites. Additionally, cell edge interference and its impact on the end user is only expected to increase as autonomous vehicles, the Internet of Things (IoT) and virtual reality (VR) applications impose additional capacity demands and latency requirements.
The next generation 5G network infrastructure investments are needed to address these issues. Among many options, one technology known as massive MIMO holds the most promise to dramatically increase cellular capacity by creating sharper antenna beam patterns with many antenna elements to transmit and receive RF signals in parallel. This huge increase in the number of antennas provides a big boost to the amount of data streams that such systems can handle compared to today’s base stations. As a result, massive MIMO is now considered a foundational technology for future 5G networks. Massive MIMO offers significant gains in wireless data rates and link reliability, allowing for video consumption from more users in a dense area without consuming additional radio spectrum or causing interference.
Massive MIMO Offers a Path Forward
On a massive MIMO base station, many antenna elements (for example, 48 or 64 or hundreds) are placed in a planar arrangement known as the antenna array. In an example of 64 antenna elements, a planar array of 8 x 8 is formed. As a result of deploying so many antenna elements, at any moment, there are, for example, 64 transmit signals leaving the antenna array and 64 signals coming into the antenna array. The biggest challenge for a massive MIMO system is to ensure the signals are aligned in time and phase with respect to each other. This challenge has throttled introduction of Massive MIMO solutions into today’s network. Only one equipment manufacturer, Blue Danube Systems, has proven capable of overcoming this challenge, using hybrid Massive MIMO, a technique combining both digital and analog versions of beamforming, a signal processing technology used to direct the transmission of radio signals. This hybrid approach to massive MIMO avoids some of the problems typical of massive MIMO systems by leveraging RF coherency.
As the 64 signals are transmitted from the antenna array, they may incur different delays and phase-shifts while traveling through different physical paths, also known as RF chains. If the time and phase alignment at the antenna array have few relative phase errors between the 64 signals (it is perfect or nearly perfect), then the system is coherent over the entire array. The result is a very sharp and accurate antenna beam to the targeted area, delivering a powerful stream of coverage. Conversely, without a coherent system, the result is a suboptimal antenna beam not pointing in the precise right direction. That means users are not benefitting from a big boost in RF signal like they would if RF coherency had been achieved. At the cell edge, the need for RF coherency is magnified because users are generally further from the base station, and there can be more interference from adjacent cell sites, both of which can cause phase errors and impact call and video quality.
Despite the prevalent view that Massive MIMO systems will be central to 5G networks, until recently, it had not been clearly proven the technology is deployable beyond isolated high-demand sectors, where effects like adjacent cell interference must be addressed. In fact, common digital-only Massive MIMO implementations typically operate as closed single-sector solutions, spilling unwanted RF energy across cell edges and potentially degrading adjacent sector performance.
Beyond Theory: Reducing Cell Edge Interference in the Field
In a recent commercial deployment at a North American wireless carrier, Blue Danube Systems proved its hybrid approach to Massive MIMO could enable a ubiquitous 5G network and deliver measurable improvement in network capacity and end user experience.
This wireless operator needed to deliver higher capacity to some key areas of its network. In these areas, users form time-variant hotspots due to the locations of shopping areas and restaurants between cell sites. Additionally (because of schools in the target deployment area), this operator experienced repeating cycles of heavy traffic at school drop-off times, followed by almost no traffic during school hours, and then another surge in demand immediately after school. These are the types of challenges operators face daily because they need flexible, intelligent systems deployed in the network to address changing customer use patterns. This operator noted that areas where multiple cell sites intersected experienced particularly poor performance due to cell edge interference. The combination of these time-variant hotspots and cell edge interference generated significant support calls complaining of poor network coverage.
To resolve the problem, this North American wireless carrier deployed a multi-site hybrid Massive MIMO solution that could dynamically change the antenna pattern (beam shapes) by pointing the RF energy to where users were and away from where users were not. This resulted in much better signal quality and a dramtic increase in Signal to Interference and Noise Ratio (SINR), a critical measure of network performance as it impacts end users.
As the deployment demonstrated, the solution was ideal for overcoming the time-variant user distribution challenges. Its software-enabled technology can direct RF beams to areas around the schools at the crucial times (before and after school), and then shift those beams to shopping areas or elsewhere at other times. Other solutions struggle with time and location variant challenges because they rely on processing massive amounts of data derived from customer devices to manage the channel characteristics for those customers. Those solutions cannot adapt as quickly or as predictably as the Blue Danube solution.
Historically, it has been difficult to quantify how much improvement is delivered to end users. In this case, Blue Danube leveraged Rohde & Schwarz’s testing equipment to accurately measure end user experiences with video applications and to quantify the amount of improvement delivered because of the Massive MIMO implementation. The Qualipoc is a handheld tool that is very convenient to carry around for drive or walk tests. Blue Danube and the operator’s engineers carried these tools to key areas where the carrier originally reported the problems (such as cell edges) and measured SINR before the Blue Danube system was installed. Qualipoc’s comprehensive drive test technology captures the current network situation on the same devices used by end users and measures voice, data and video performance as a customer would experience it. This enables an authentic mapping of the mobile radio network as experienced by the customer.
By comparing SINR before and after the implementation, Blue Danube demonstrated a 5 to 7 dB improvement in SINR at the cell edge. For the end user, this improvement can mean the difference between being unable to watch a Standard Definition video or even complete a call at the cell edge to viewing an uninterrupted High Definition video. This improved SINR score translates into a 70 percent improvement in individual user download speed. Furthermore, R&S Qualipoc measures Video Mean Opinion Score (VMOS) which attaches a numerical value to the quality of viewing a video. During this deployment, the system delivered a significant improvement in the VMOS score from 3.5 to 4.5, which is the difference of watching video with repeated buffering and interruptions versus watching a flawless HD video.
Overcoming the technical challenges of RF coherency and precise dynamic beam control, the system delivered outstanding capacity improvement for the network operator. More importantly, the deployment enabled testing of performance in a multi-site or cluster environment.
Conclusion:
Building a Massive MIMO-enabled 5G network will require both technology solutions that successfully deliver enhanced capacity for the network and the equipment to measure the actual end user experience. As demonstrated with a North American wireless carrier, a hybrid Massive MIMO solution can increase network capacity and maintain high performance at the cell edge. Use of the Qualipoc quantifies the benefits to customers by accurately measuring video performance across the network. These solutions move the industry one step closer to the robust, 5G network capable to supporting rapidly evolving devices and applications that will be dependent upon it. Even better for carriers experiencing capacity constraints now, both solutions are deployment ready today.
