In the quest to satisfy the need for increased mobile broadband capacity and better quality of service in urban environments, operators are accelerating the deployment of heterogeneous networks (HetNets). These are mixed networks that include a combination of macrocells, and small cells – microcells and picocells.
According to the Small Cells Forum, small cell deployments have now reached more than 10 million worldwide, and are now considered to be a key part of operator strategies. Although some of these cells are residential installations, a growing number are being deployed in HetNets. Adding small cells can fill in extra capacity where there is a high density of mobile users, and allow operators to better manage the load on their networks, but they need careful planning and coordination. When mobile operators deploy small cells, they often find that they do not deliver the expected user experience.
Particular problems can be caused by interference with the macrocell at the edges of the small cell coverage area, which can result in a serious deterioration in user experience. Fortunately LTE-Advanced offers a range of techniques for mitigating interference by coordinating traffic and scheduling, but these present many challenges both in implementation and in validating the user experience improvement.
The interference management techniques include eICIC (enhanced Inter-Cell Interference Coordination), feICIC (further enhanced ICIC) and CoMP (Coordinated Multipoint transmission/reception), which can all help to reduce cell-edge issues. By testing these features in the network under real traffic conditions, the operator can ensure that they are delivering the required improvement in user experience.
eICIC and feICIC both use radio resource management techniques to reduce interference at the cell edges, using an autonomous scheduler to dynamically distribute bandwidth and power resources between cell users depending on metrics of the interference level they are experiencing.
eICIC requires coordination of the transmissions between a macrocell and each of the small cell nodes whose coverage area overlaps with it. Normally the mobile terminal will connect to the cell that has the strongest downlink signal. However to ensure that the small cell is serving enough users its coverage area can be extended by a technique known as cell range expansion (CRE). This is obtained by introducing a handover bias allowing traffic associated with users who would normally be just outside the area of small cell coverage be offloaded from the heavily-loaded macrocells to the more lightly-loaded small cells, in order to achieve better load balancing and system performance in the HetNet. With feICIC the cell expansion is spread even further by increasing the biasing level from approximately 6dB to more than 9dB, which is achieved by implementing interference cancellation in the handset.
With CRE, a mobile terminal operating at the cell edge of a picocell will experience significant interference from the macrocell. This interference can be mitigated by preventing the macrocell from transmitting data during certain subframes, known as Almost Blank Subframes (ABS), and giving the small cells the opportunity to perform CRE during these ’protected’ subframes on occasions when the macrocell is loaded too heavily. This load balancing is an important component of Self Optimising Networks (SON), a range of techniques that promote the overall improvement of network performance and energy saving.
Testing a network employing eICIC or feICIC means that the network tester must be able to apply the relevant measurement procedures in order to feed back correct and reliable information to the network. The Cobham Wireless TM500 network tester family can be used to verify the correlation between the measurements reported by the mobile device and the cell signalling patterns, thus validating the interference management.
The addition of CoMP goes one step further in achieving better overall network capacity, by coordinating transmission and reception between different transmitting and receiving cells. It achieves this through the use of load balancing, coordinated scheduling, and the management of signal power and interference, allowing improved downlink data throughput, especially near the cell edges, due to reduced interference and an increase in received power. Uplink received signal quality and cell edge coverage is also improved by simultaneous coordinated reception from different receiving points on the network side. Again it is challenging to validate due to the requirement for rapid information exchange and the coordination of shared and centralized processing between multiple transmitting points.