In this chapter, we described the outline and contributions of the thesis. Rest of the thesis is organized as follows. In chapter 2, we describe the advantages of decoupled access for downlink and uplink in the enterprise Femtocell environments. Then, we propose an efficient downlink offloading algorithm and study the performance of the proposed system in both uniform and non-uniform traffic load scenarios.
In chapter 3, to reduce the unnecessary handovers or ping-pong effect in enterprise building environments, we propose a handover and SINR optimized deployment of LTE Femtocells and study the performance in terms of throughput by comparing it with arbitrary and center placement schemes. In chapter 4, we design a efficient
power control algorithm to reduce the impact of cross-tier interference to OU Es and in chapter 5, we consider both uplink and downlink interference while Femto planning. Also we ensure that energy consumption in Green HetNet (uplink) building is less when compare to center placement. In chapter 6, to improve the SINR in LTE HetNet system, we adopt the D2D based relay concept to propose a D2D pair selection algorithm and compare the SINR performance with that of a D2D Mixed Integer Linear Programming (MILP) model.
In chapter 7, a novel resource allocation and power control mechanism for HAFs is proposed. Also, we have shown the trade off between the closed access and hybrid access Femtocell. In chapter 8, we compare the above proposed solutions (described in chapters 6, 7 and 8) in terms of throughput and operator revenues. In chapter 9, we propose a distributed resource allocation and interference management algorithm for LTE Femtocells which dynamically increases or decreases the radius of inner regions to avoid co-tier interference among Femto BSs. Finally, we summarize the contributions of the thesis and discuss the possible future extensions in chapter 10.
Chapter 2
On Femto Placement and
Decoupled Access for Downlink
and Uplink in Enterprise
Environments
2.1
Introduction
Dense deployment of Femtos in enterprise environments [27] necessitates the need for their optimal placement to guarantee good signal strength to all indoor UEs and to minimize coverage holes. In this work, we formulate a Mixed Integer Linear Programming (MILP) model for the optimal placement of Femtos. In a typical indoor scenario with Femtocells, the uplink load of a cell would more or less be the same in the entire building, but the downlink load would vary widely from one Femto to other depending on the number of UEs being served [28,29] and their traffic demands. In traditional cellular networks (i.e., coupled access systems), the uplink access and downlink access are coupled to the same cell as shown in Figure 2.1. Here, the user utuses F emto2 for both uplink and downlink communication because the signal
strength fromF emto2 is higher than that ofF emto1. Suppose a Femto is fully loaded
when compared to its neighboring Femtos, the traditional offloading or load balancing algorithms [30, 31] will shift some of the UEs for both uplink and downlink from the over loaded cell to one of less loaded cells (target cells) provided that these UEs still could get connected to the target cell. This type of offloading is a forced handover based on the load but not based on signal strength, because the signal strength when
connected to the initial serving Femto will be high compared to the target Femto. For example in Figure 2.1, we observe that F emto2 is more loaded (by assuming more
traffic load when there are more UEs in a cell) hence the userutcan be offloaded to the
neighboring Femto i.e., F emto1. In a coupled access system, as shown in Figure 2.2,
after offloading, ut uses F emto1 for both uplink and downlink communication. Since
ut and F emto1 are separated by a wall, ut has to transmit with higher power to
achieve good UL SNR in F emto1 compared to when it was connected to F emto2.
By doing this kind of offloading, the overall system throughput will increase but the uplink power of the shifted UEs would increase and thereby drain their batteries faster.
Figure 2.1: Coupled Access System before offloadingUt toF emto1
Figure 2.2: Coupled Access System after offloading Ut toF emto1 from F emto2
In order to reduce the battery drain from UEs and to improve the downlink data rate, one could use the Decoupled Uplink and Downlink (DUD) access method [23] i.e., uplink connected to the closest Femto and downlink to a less loaded Femto. For example in Figure 2.3, we observe that user ut connects toF emto1 for downlink and
Figure 2.3: Decoupled Access System after offloading only downlink of Ut toF emto1
fromF emto2
F emto2 for uplink communication. Before doing this, the placement of Femtos should
be optimal inside the building to attain a desirable SNR for indoor UEs.
In the present work, we look into the problem of optimal Femto placement in indoor environments to obtain a desirable SNR at each location inside the building with out any coverage holes. Two major parameters that determine the optimal Femto locations include (i) distance between Femto and the farthest point inside the building and (ii) the minimum SNR needed by each UE. Solving for optimal placement of Femtos by considering the above parameters results in a non-convex optimization problem [32]. We further simplify this non-convex problem to fit into MILP model and solve it using GAMS tool [33]. After Femtos are placed optimally, to increase the downlink throughput and reduce battery drain, we propose an offloading algorithm in DUD access system.
2.1.1
Organization of this Chapter
The rest of the chapter is organized as follows. Section 2.2 presents related work on Femto placement and decoupled access systems. Section 2.3 describes the proposed Femto placement model. Section 2.4 presents the proposed efficient offloading algo- rithm for DUD access systems. In Section 2.5, we show the performance results of the proposed Femto placement model and offloading algorithm in a two-storey enterprise building scenario. Finally, Section 2.6 summarizes the work.