Two key traits of 5G cellular networks are much higher base station (BS) densities - especially in the case of low-power BSs - and the use of massive MIMO at these BSs. This paper explores how massive MIMO can be used to jointly maximize the offloading gains and minimize the interference challenges arising from adding small cells. We consider two interference management approaches: joint transmission (JT) with local precoding, where users are served simultaneously by multiple BSs without requiring channel state information exchanges among cooperating BSs, and resource blanking, where some macro BS resources are left blank to reduce the interference in the small cell downlink. A key advantage offered by massive MIMO is channel hardening, which enables to predict instantaneous rates a priori. This allows us to develop a unified framework, where resource allocation is cast as a network utility maximization (NUM) problem, and to demonstrate large gains in cell-edge rates based on the NUM solution. We propose an efficient dual subgradient based algorithm, which converges towards the NUM solution. A scheduling scheme is also proposed to approach the NUM solution. Simulations illustrate more than 2x rate gain for 10th percentile users vs. an optimal association without interference management.
@cite_28: 
@cite_1: Interference is a major performance bottleneck in Heterogeneous Network (HetNet) due to its multi-tier structure. We propose almost blank resource block (ABRB) for interference control in HetNet. When an ABRB is scheduled in a macro BS, a resource block (RB) with blank payload is transmitted and this eliminates the interference from this macro BS to the pico BSs. We study a two timescale hierarchical radio resource management (RRM) scheme for HetNet with dynamic ABRB control. The long term controls, such as dynamic ABRB, are adaptive to the large scale fading at a RRM server for co-Tier and cross-Tier interference control. The short term control (user scheduling) is adaptive to the local channel state information at each BS to exploit the multi-user diversity. The two timescale optimization problem is challenging due to the exponentially large solution space. We exploit the sparsity in the interference graph of the HetNet topology and derive structural properties for the optimal ABRB control. Based on that, we propose a two timescale alternative optimization solution for user scheduling and ABRB control. The solution has low complexity and is asymptotically optimal at high SNR. Simulations show that the proposed solution has significant gain over various baselines.
@cite_52: Enhanced Inter-cell Interference Co-ordination (eICIC) is a time-domain multiplexing technique for improving the performance of legacy co-channel Heterogeneous Networks (HetNets). eICIC offers several benefits, including a more equitable distribution of user traffic across the macro and embedded pico cells (i.e., load balancing), in turn leading to better pico cell utilizations and better edge user throughputs. eICIC uses two mechanisms to achieve load balancing: (i) a cell selection bias to increase the pico coverage area, enabling the pico to attract more users, and (ii) macro muting ("Almost Blank Sub-frame", ABS) to improve SINRs of range extended pico users. Network load in the cellular system varies continuously as a result of user mobility and traffic dynamics (the varying amount of data pending for a user - arising from packet arrivals and eventual departures). Previous work did not consider dynamically changing network conditions in HetNets. Hence, they studied the benefits of eICIC over legacy HetNets arising from static optimization of eICIC parameters. Our approach is dynamic, and further improves performance by keeping the HetNet continuously optimized for improved user experience, by adapting the ABS in response to dynamic variations in network load. We present several analytical formulations, which allow for simple optimizations and an intuitive understanding of the desired system response to load variation. Exhaustive system simulations illustrate the performance gains along different dimensions, such as spectral efficiency, fairness, mean file transfer times, number of file transmissions, number of file drops, and mean queue lengths. Furthermore, we study the impact of different mobility scenarios, traffic mixes, and adaptation rate. We also provide a brief discussion of practical considerations in implementing Dynamic eICIC.
@cite_45: The rate distribution in heterogeneous networks (HetNets) greatly benefits from load balancing, by which mobile users are pushed onto lightly-loaded small cells despite the resulting loss in SINR. This offloading can be made more aggressive and robust if the macrocells leave a fraction of time frequency resource blank, which reduces the interference to the offloaded users. We investigate the joint optimization of this technique - referred to in 3GPP as enhanced intercell interference coordination (eICIC) via almost blank subframes (ABSs) - with offloading in this paper. Although the joint cell association and blank resource (BR) problem is nominally combinatorial, by allowing users to associate with multiple base stations (BSs), the problem becomes convex, and upper bounds the performance versus a binary association. We show both theoretically and through simulation that the optimal solution of the relaxed problem still results in an association that is mostly binary. The optimal association differs significantly when the macrocell is on or off; in particular the offloading can be much more aggressive when the resource is left blank by macro BSs. Further, we observe that jointly optimizing the offloading with BR is important. The rate gain for cell edge users (the worst 3-10 ) is very large - on the order of 5-10x - versus a naive association strategy without macrocell blanking.
@cite_47: The success of LTE heterogeneous networks (HetNets) with macrocells and picocells critically depends on efficient spectrum sharing between high-power macros and low-power picos. Two important challenges in this context are: 1) determining the amount of radio resources that macrocells should offer to picocells, and 2) determining the association rules that decide which user equipments (UEs) should associate with picos. In this paper, we develop a novel algorithm to solve these two coupled problems in a joint manner. Our algorithm has provable guarantee, and furthermore, it accounts for network topology, traffic load, and macro-pico interference map. Our solution is standard compliant and can be implemented using the notion of Almost Blank Subframes (ABS) and Cell Selection Bias (CSB) proposed by LTE standards. We also show extensive evaluations using RF plan from a real network and discuss self-optimized networking (SON)-based enhanced inter-cell interference coordination (eICIC) implementation.
@cite_13: 3GPP LTE-Advanced has recently been investigating heterogeneous network (HetNet) deployments as a cost effective way to deal with the unrelenting traffic demand. HetNets consist of a mix of macrocells, remote radio heads, and low-power nodes such as picocells, femtocells, and relays. Leveraging network topology, increasing the proximity between the access network and the end users, has the potential to provide the next significant performance leap in wireless networks, improving spatial spectrum reuse and enhancing indoor coverage. Nevertheless, deployment of a large number of small cells overlaying the macrocells is not without new technical challenges. In this article, we present the concept of heterogeneous networks and also describe the major technical challenges associated with such network architecture. We focus in particular on the standardization activities within the 3GPP related to enhanced intercell interference coordination.
@cite_25: In heterogeneous networks, a macro cell can cause excessive interference to users in co-channel pico cells. In Release 10 of 3GPP's LTE system, enhanced Inter-Cell Interference Coordination (eICIC) has been introduced to reduce the interference experienced by pico users by having the macro mute some of its subframes. This is a tradeoff, because the benefit to pico users comes at the cost of the macro sacrificing a portion of its resources. This tradeoff is also influenced by the determination of which users are offloaded from the macro to the pico. We formulate the joint optimization of the proportion of muted sub-frames and the assignment of users to macro and pico cells as a network-wide utility maximization problem, and obtain an analytical characterization of the optimal solution. We propose an iterative algorithm that successively improves the assignment of users to cells and the muting proportion, and prove its convergence to the optimal solution.
@cite_11: 
. As the macrocells that users are offloaded from now become strong interferers for these offloaded users, the increased interference eats into the gains offered by load balancing. This motivates us to jointly consider user association and interference management. Besides CoMP, another popular interference management approach is to leave some macro resource blocks (RBs) blank, similar to enhanced intercell interference coordination (eICIC) in 3GPP @cite_13 . The key difference between RB blanking in our work and eICIC is that eICIC focuses on the time domain, while in this work blanking is applied in both time and frequency domains. We call the RBs where macro BSs are muted the , while the rest of RBs are called . Several works have considered the joint problem of user association and RB blanking. For example, @cite_52 @cite_1 proposes a dynamic approach adapting the muting duty cycle to load variations, while @cite_45 @cite_25 @cite_11 @cite_47 @cite_28 consider a more static approach.