Interference-aware

Interference-aware HO decision making is a key enabler for shifting to the femtocell communication paradigm. In this class we include algorithms that account for the co-tier and cross-tier interference by using parameters such as the interference level at the cell sites [66] or the RSQ at the UEs [67]-[70]. In the following, we discuss three representative algorithms of the interference-aware class.

a. Handover Decision Policy for Reducing Power Transmissions in the Two-Tier Network

The proposed HO decision policy in [66] aims at reducing the UE power transmissions in the two-tier macrocell-femtocell LTE-Advanced network. To achieve this, the policy estimates the mean UE transmit power on a per candidate cell basis based on a) a prescribed mean SINR target and b) standard UE and E- UTRAN measurements. The estimation outcome is used for handing over to the candidate cell that minimizes the mean UE transmit power. The proposed policy applies to the multiple-macrocell multiple-femtocell HO decision scenario, while it is integrated in the standard RSS-based procedure by utilizing an adaptive HHM. The adaptive HHM is used to transform the relative RSS comparison with HHM to a relative mean UE transmit power comparison with HHM. Note that a fixed HHM is used as well, to mitigate the negative impact of user mobility and reduce the ping-pong effect.

Figure 65: Xenakis et al. interference-aware HO policy [66]

The proposed policy is depicted in Figure 65. Upon HO decision triggering, the serving cell signals a HO context request to the candidate cells in order to acquire a) the RIP at the cell site, b) the downlink RS transmit power, and c) the operating band of the cell. The mean UE transmit power of the serving cell policy is

subsequently estimated by using a) the RSRP measurement, b) the parameters for the candidate cell status and b) the prescribed mean SINR target. Depending on the operating band of the candidate cell, the adaptive HHM is evaluated on per candidate cell basis and a HO is initiated to the candidate cell that minimizes the mean UE transmit power.

The proposed policy is compatible with the LTE-A system as it utilizes standard UE and E-UTRAN measurements to adapt the HHM. The performance of the policy is assessed by using the widely accepted evaluation methodology of the Small Cell Forum [123]. The incorporation of the actual RS transmit power and RIP of the candidate cell is another strong feature of the proposed policy, which is shown to a) reduce the mean UE and cell transmit power, and b) lower the interference level at the UE and (H)eNBs sites. However, the signaling procedure for commuting the HO decision parameters to the serving cell is only briefly discussed by the authors. On the other hand, even though simulation results demonstrate the impact of the fixed HHM on the performance of the algorithm, a more detailed HHM selection methodology is required to optimize the performance of the proposed policy.

b. Signal Quality based Handover Algorithm for the Macrocell-Femtocell LTE- Advanced Network

A RSQ-based algorithm is proposed in [67] aiming to mitigate the number of unnecessary HOs in the presence of femtocells. The proposed algorithm applies to the scenario where the UE is served by a macrocell and enters the coverage of a femtocell. The fundamental operation of the algorithm is similar to the one of the algorithms in [68][69]. The HO decision is reached by taking into account the RSRP, RSRQ and available bandwidth parameters. This algorithm accounts for the impact of the interference by using the RSQ measurements provided by the UE. The proposed algorithm is presented in Figure 66.

The algorithm continuously monitors the RSRP and RSRQ of the target femtocell if at least one of the following conditions apply: a) the RSRP of the femtocell is lower than a prescribed RSRP threshold, denoted by _, , b) the RSRP of the femtocell does not exceed the , threshold for over a prescribed time interval , or c) the RSRQ of the femtocell is lower than a prescribed RSRQ threshold, denoted by _, . On the other hand, the algorithm handovers to the femtocell if a) the RSRP of the serving macrocell is lower than a prescribed RSRP threshold, denoted by _, , b) the RSRQ of the femtocell is greater than the one of the macrocell and c) the femtocell can support the bandwidth requirements of the UE. A handover to the femtocell is also initiated when a) none of the conditions for continuous RSRP and RSRQ monitoring are in effect, b) the RSRQ of the femtocell is greater than the one of the serving macrocell and c) the bandwidth requirements of the UE are satisfied. Note that the outcome of the HO decision is the same either if the condition for a higher RSRQ for the femtocell is satisfied or if the RSRQ of the target femtocell is greater than the absolute threshold _, .

Figure 66: Yang et al. HO algorithm [67]

Among the strong features of the proposed algorithm is the use of preliminary admission control prior to the HO execution, which is expected to eliminate the HO failure probability due to admission control. The incorporation of the RSQ measurements is another strong feature of the algorithm, which is expected to enhance the SINR performance at the UEs. However, the absence of a HHM during the relative RSQ comparison may unpredictably raise the HO probability in the presence of deep channel fading. A more detailed methodology is required to select the RSRP and RSRQ thresholds, while the QoS maintenance and UE energy consumption overhead for continuously monitoring the RSRQ and RSRP should also be examined.

c. Adaptive Hysteresis Margin HO Algorithm in Femtocell Networks

An adaptive HHM approach is presented in [70] to lower the number of unnecessary HOs in the two-tier macrocell-femtocell network. The authors highlight that the interference level at the UEs majorly affects the shape of the femtocell service area, which should be reassessed in the context of the RSQ at the UEs. The proposed algorithm compares the RSQ status of the serving and the target cells by using an adaptive HHM. The HHM is adapted with respect to the RSQ at the UE and the estimated path loss. The algorithm applies to the scenario where the UE is served from a macrocell and enters the proximity of a

femtocell.

Figure 67: Becvar et al. HO algorithm [70]

The flowchart version of the proposed algorithm is depicted in Figure 67. Upon HO decision triggering, the UE performs RSRQ measurements to evaluate the RSQ status of the macrocell and femtocell stations. The HHM is subsequently adapted as follows:

= max , ∙ 1 − 10

( )

(6.4) where denotes a minimum HHM value, a maximum HHM value, the path loss exponent between the UE and the cell, the minimum required RSRQ threshold for sustaining service continuity with the network, and an algorithm-related parameter. A HO to the femtocell is initiated when the RSRQ of the target femtocell is greater than the RSRQ of the serving macrocell plus the adaptive HHM.

Among the strong features of the proposed algorithm is the use of distance estimation based on the RSQ reported by the UEs. The proposed algorithm also requires minimum interventions to the standard (H)eNB functionality as it can be employed by adapting the HHM. The performance of the algorithm is validated by using the evaluation methodology in [123], while various system-level simulation results are derived as well. Nevertheless, the selection of an appropriate path loss exponent can be very challenging in real-life deployment scenarios, if we consider the NLOS conditions and the fast variations of the wireless medium. Even though the authors provide guidelines on how to calculate the

value, a more detailed methodology is required to optimize this parameter in real- time. More extensive simulation results are also required to investigate the impact of the proposed RSQ-based algorithm on the interference and energy consumption of nearby cells. The performance of the proposed algorithm should be compared against other non RSQ-based algorithms as well.