Recently, Dynamic Time Division Duplex (TDD) has been proposed to handle the asymmetry of traffic demand between DownLink (DL) and UpLink (UL) in Heterogeneous Networks (HetNets). However, for mixed traffic consisting of best effort traffic and soft Quality of Service (QoS) traffic, the resource allocation problem has not been adequately studied in Dynamic TDD HetNets. In this paper, we focus on such problem in a two-tier HetNet with co-channel deployment of one Macro cell Base Station (MBS) and multiple Small cell Base Stations (SBSs) in hotspots. Different from existing work, we introduce low power almost blank subframes to alleviate MBS-to-SBS interference which is inherent in TDD operation. To tackle the resource allocation problem, we propose a two-step strategy. First, from the view point of base stations, we propose a transmission protocol and perform time resource allocation by formulating and solving a network capacity maximization problem under DL UL traffic demands. Second, from the view point of User Equipments (UEs), we formulate their resource allocation as a Network Utility Maximization (NUM) problem. An efficient iterative algorithm is proposed to solve the NUM problem. Simulations show the advantage of the proposed algorithm in terms of network throughput and UE QoS satisfaction level.
In @cite_14 @cite_28 @cite_21 @cite_24 , ABS based interference mitigation mechanisms have been introduced for dynamic TDD HetNets. In these mechanisms, MBSs blank some subframes as ABS to avoid severe interference to small cells. In @cite_14 , MBSs and SBSs configured synchronous DL and UL transmissions on non-ABS, and SBSs applied dynamic TDD on ABS. Similarly, in @cite_28 @cite_21 @cite_24 , MBSs and SBSs configured synchronous DL transmissions on non-ABS. However, SBSs applied dynamic TDD on not only ABS, but also subframes where MBSs configured UL transmissions.
@cite_28 @cite_14 @cite_21 @cite_24
2072460547 1968081294 2023633390 1979201349
Future wireless communication systems feature heterogeneous networks (HetNets), with small cells underlying existing macrocells. In order to maximize the off-loading benefits of small cells and mitigate the interference from the macrocell tier to the small cell tier, cell range expansion (CRE) and almost blank subframes (ABSs) have been designed for small cells and macrocells, respectively. Besides, enhanced 4th generation (4G) networks are also envisaged to adopt dynamic time division duplexing (TDD) transmissions for small cells to adapt their communication service to the fast variation of downlink (DL) and uplink (UL) traffic demands. However, up to now, it is still unclear whether it is technically feasible to introduce dynamic TDD into HetNets. In this paper, we investigate this fundamental problem and propose a feasible scheme to enable small cell dynamic TDD transmissions in HetNets. Simulation results show that compared with the static TDD scheme with CRE and ABS operations, the proposed scheme can achieve superior performance gains in terms of DL and UL packet throughputs when the traffic load is low to medium, at the expense of introducing the DL-to-UL interference cancellation (IC) functionality in macrocell base stations (BSs) and or small cell BSs. Almost-blank subframe (ABSF) is a time-domain technique, proposed by the 3GPP to handle Inter-Cell Interference (ICI) in heterogeneous network environments (HetNet). We consider a HetNet environment comprised of a macro-cell and femto-cells distributed across the macro-cell area. We propose a novel approach, called ABSF offsetting, to reduce the blanking rate at the femto-cells while preserving the required optimal blanking rate at the macro-cell. We also study the problem of optimal resource partitioning and offset assignment in the ABSF mode. The proposed solution for the problem is based on multistage Nash bargaining. The performance of the optimal resource partitioning, and ABSF offsetting is evaluated through simulations. The results show that the throughput of the macro-cell is improved, while the degradation in the aggregate femto-cell throughput is reduced due to the reduction in the blanking rate due to offsetting. The simulation results also demonstrate the fairness of the ABSF offsetting with the fairness index approaching 1 among the macro-cell UEs at low loads. We consider a heterogeneous cellular network (HetNet) where a macrocell tier with a large antenna array base station (BS) is overlaid with a dense tier of small cells (SCs). We investigate the potential benefits of incorporating a massive MIMO BS in a TDD-based HetNet and we provide analytical expressions for the coverage probability and the area spectral efficiency using stochastic geometry. The duplexing mode in which SCs should operate during uplink macrocell transmissions is optimized. Furthermore, we consider a reverse TDD scheme, in which the massive MIMO BS can estimate the SC interference covariance matrix. Our results suggest that significant throughput improvement can be achieved by exploiting interference nulling and implicit coordination across the tiers due to flexible and asymmetric TDD operation. 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.