Friday, April 19, 2024

Enhancing 4G mobile user experience in Heterogeneous Networks

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Nicola Logli, Cobham Wireless

Heterogeneous networks (HetNets) are now being deployed along with Self-Organizing Networks (SON) to address the need for increased network capacity. A HetNet comprises a combination of macrocells or eNodeBs with small cells (microcells, picocells and femtocells) relay eNodeBs and remote radio heads (RRH).

It is often seen that when mobile operators deploy small cells, they do not tend to deliver the expected user experience. The primary reason for the degradation of quality and service with HetNets is the poor cell-edge performance due to lack of traffic coordination and interference management between small cells and macrocells. The 3GPP standards for LTE-Advanced incorporate a range of techniques for mitigating cell-edge interference issues, but there are many challenges introduced, both during the process of implementation and then in the ability to validate the improvement in user experience once they are deployed in the network. This article explains how eICIC, feICIC and CoMP techniques can help reduce cell-edge issues, and also how the operator can test these features in the network so as to ensure that they are delivering the required improvement in user experience under realistic traffic conditions.

Interference coordination

3GPP introduced ICIC (Inter-Cell Interference Coordination) to reduce interference at the cell edges by using radio resource management (RRM) techniques in the frequency domain – using an autonomous scheduler to dynamically distribute bandwidth and power resources between cell users. Here the users are categorised according to their Signal-to-Noise-plus-Interference Ratio (SNIR), and different reuse factors are applied according to this indicator.

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This scheme was extended in order to include time domain management of the interference. This is called eICIC (enhanced ICIC), which is much more effective for users in a close proximity to a small cell. eICIC is especially designed to improve cell edge performance and coverage in HetNet deployment scenarios where the coverage areas of nodes of different types – macrocells, small cells and RRH are partially overlapping, and differs from ICIC by not being transparent to the mobile handset or UE (User Equipment).

eICIC requires coordination between each of the network nodes that communicate with each other through the X2 interface. In a typical application, a macrocell whose coverage area overlaps with that of one or more small cells can coordinate its transmissions with these nodes. The coverage of a small cell can be extended by applying the cell selection bias offset values, which is commonly known as cell range expansion (CRE) bias. This offloads traffic (from UEs that otherwise would not be considered in the small cell coverage area) from the heavily-loaded macrocells to the lightly-loaded small cells in order to achieve better system performance in the HetNet. In eICIC, the maximum CRE bias value is 6 dB, because a cell may not be detectable under -6 dB signal-to-noise ratio (SNR).

With CRE bias, a UE operating at the cell edge of a picocell will experience a significant level of interference from the macrocell. This interference can be reduced by limiting the macrocell transmissions to DL Common Reference Signal (CRS) alone, without scheduling any data transmission, during certain subframes called Almost Blank Subframes (ABS). This technique results in a lower interference level in the UEs at the cell edge of the microcell or picocells, and gives the microcell or picocells the opportunity to perform CRE in order to increase the coverage area during these protected subframes. Cell range expansion techniques are used for offloading some of the UEs from the macrocell to the smaller cell. This technique is used to achieve better results in load balancing when the macrocells are loaded too heavily. The UE that has been offloaded needs to be scheduled from the smaller cell during the low interference ABS. Load balancing is an important constituent of Self-Optimising Networks (SON), which includes a range of techniques promoting energy saving and of network performance improvement.


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