Tong En

An improved graph coloring based small cell discovery scheme in LTE hyper-dense networks

Efficient discovery of multiple small cells is important to features such as small cell on/off, load balancing, CoMP (Coordinated Multi-point Transmission), e-ICIC (enhanced-Inter-Cell Interference Coordination) in LTE (Long Term Evolution) hyper-dense networks. However, severe interference in the Hyper-Dense Networks imposes great difficulty on efficient discovery of small cells. This paper proposes an improved graph coloring based scheme to facilitate the discovery of multiple small cells in Hyper-Dense Networks. Our proposed scheme is to divide small cells that are near to each other into different groups and let each group take turns to transmit synchronization signals so that interference between small cells are reduced. Graph coloring theory is employed in the division of small cells to guarantee that small cells within a certain distance are divided into different groups. Simulation results shows that using the proposed scheme detection probability of top 10 small cells is greatly improved compared to conventional scheme.

A practical eNB off/on based energy saving scheme for real LTE networks

In this paper, a low-complexity practical energy saving algorithm by switching off/on some eNBs in a real dense urban scenario considering historical and real-time eNB load is proposed. First, eNBs are ranked according to their loads in an ascending order and the first eNB in the list with load decreasing and smaller than a low threshold is pre-selected as target switching off cell. Then, the effect of the target switching off eNB on neighbour eNBs is evaluated. The target eNB switches-off while the load of neighbour eNBs after the eNB switches off is smaller than another threshold. Since estimation of the additional load on the neighbour eNBs due to the switch-off eNB is of high complexity, a fast estimation algorithm considering the whole eNB load by a traffic load conversion coefficient is proposed. Third, the switching-off eNB can be switched on by the active eNBs in a distributed way. Simulation results show that the proposed energy saving scheme can save up to 24% energy consumption.

A low complexity energy efficiency optimization algorithm based on optimal switching-off eNB selection in LTE networks

In this paper, a low complexity algorithm is proposed to improve energy efficiency in LTE networks. Energy efficiency optimization issue is formulated as NP-hard problem which requires high computational cost due to optimal exhaustive search (ES). Then a low complexity energy efficiency optimization algorithm (LCEEO) based on optimal switching-off eNB selection is proposed. With LCEEO, eNBs will be pre-ordered in descending order according to load increments brought into network. First eNB is selected to switch off according to pre-order. Then users in selected eNB will be handed over to other eNBs if quality of service (QoS) for users can be guaranteed. After that, selected eNB is switched off if network energy can be saved. Rest eNBs will be evaluated with updated pre-ordering if any eNB is switched off. Extensive simulations demonstrate that LCEEO can achieve the optimal performance compare to exhaustive search, and the algorithm complexity is significantly reduced.

An Optimal Switching-off eNB Selection Algorithm in LTE Hyper-dense Networks

Although the application of the exhaustive search (ES) algorithm in the energy conservation strategy can realize the simultaneous switching off of multiple eNBs in the existing eNB-based (Evolved Node B) networks, it fails to satisfy the practical requirement of network deployment with the heavy computation burden. On account of this, this paper proposes an optimal switching-off eNB selection (OSS) algorithm in homogeneous networks. By selecting a certain cell within the coverage of multiple eNBs, the OSS algorithm can make an evaluation of the increment of network load caused by the switching off of various eNBs in the coverage area. Then it can sort one by one all of the eNBs that are to be switched off under the condition that the QoS (Quality of service) requirement of all of the users has been met. Afterwards, the OSS algorithm will switch the users according to the principle of least network load increment and eventually find an eNB that shows the optimal energy saving effect in sleep mode. The simulation results reveal that the OSS algorithm can satisfy the requirement of efficient energy conservation in wireless networks. Additionally, with low computational complexity, it also will facilitate network deployment. An Optimal Switching-off eNB Selection Algorithm in LTE Hyper-dense NetworksAlthough the application of the exhaustive search ES algorithm in the energy conservation strategy can realize the simultaneous switching off of multiple eNBs in the existing eNB-based Evolved Node B networks, it fails to satisfy the practical requirement of network deployment with the heavy computation burden. On account of this, this paper proposes an optimal switching-off eNB selection OSS algorithm in homogeneous networks. By selecting a certain cell within the coverage of multiple eNBs, the OSS algorithm can make an evaluation of the increment of network load caused by the switching off of various eNBs in the coverage area. Then it can sort one by one all of the eNBs that are to be switched off under the condition that the QoS Quality of service requirement of all of the users has been met. Afterwards, the OSS algorithm will switch the users according to the principle of least network load increment and eventually find an eNB that shows the optimal energy saving effect in sleep mode. The simulation results reveal that the OSS algorithm can satisfy the requirement of efficient energy conservation in wireless networks. Additionally, with low computational complexity, it also will facilitate network deployment.

A MRO scheme for dual connectivity in LTE small cell enhancement scenario

Dual connectivity is a promising architecture for the future hyper-dense wireless cellular network to meet the rapidly increasing demand of wireless data transmission. In this architecture, the control plane (C-plane) and the user plane (U-plane) are split and a User Equipment (UE) simultaneously connects to two different cells: the Primary Cell (PCell) which is in charge of the C-plane, and the Secondary Cell (SCell) which provides high data rate. In this paper, the Mobility Robustness Optimization (MRO) problem of the PCell in intra-frequency dual connectivity Long Term Evolution Small Cell Enhancement (LTE SCE) scenario is investigated. We propose a MRO scheme where the handover (HO) parameters for a UE are adjusted according to its speed, the HO historical records and the user-cluster distance. Simulation results show that the proposed scheme has a significantly better mobility performance compared with that of the baseline scheme.