Interference mitigation via successive cancellation in heterogeneous networks

Abstract

In this paper, we present practical interference management schemes in heterogeneous networks (HetNets) based on interference decoding and cancellation at the receivers. The underlying idea is based on Han-Kobayashi type message splitting (MS) technique [3]. We develop relatively low-complexity precoders that facilitate interference mitigation and maximize sumthroughput in the network. System-level simulation results for a general HetNet system are presented. It is shown that the proposed MS design along with interference coordination among the cells provides up to 57% cell average throughput gain compared with the rank-1 coordinated beamforming (CBF) scheme. The design also provides substantial throughput gain in particular for Macro cells compared with rank-adaptive CBF transmission.

Interference Mitigation via Rate-Splitting and Common Message Decoding in Cloud Radio Access Networks

“…The following proposition illustrates how problems (21) and (24) Proof. The respective formulations of problems ( 21) and ( 24) share the same objective function.…”

Interference Mitigation via Rate-Splitting and Common Message Decoding in Cloud Radio Access Networks

“…For instance, inspired by the theoretical works in [15], [16], the authors in [23] generalize this RS-CMD scheme to a practical multi-cell network showing significant achievable rate improvement by jointly designing the beamforming vectors for private and common information in RS-CMD as compared to beamforming design using TIN. In [24], the authors apply RS ideas to a practical setup of heterogeneous wireless networks. The results in [24] suggest that a significant performance gain can be reached by applying RS as compared to rank-1 coordinated beamforming schemes that adopt TIN strategy.…”

“…In [24], the authors apply RS ideas to a practical setup of heterogeneous wireless networks. The results in [24] suggest that a significant performance gain can be reached by applying RS as compared to rank-1 coordinated beamforming schemes that adopt TIN strategy. The work in [25] uses common message decoding and successive interference cancellation techniques to maximize the sum rate in multi-cell multi-user MIMO system.…”

“…The functions in ( 26), ( 31)-( 34) and ( 37)-( 38) define a convex feasible set, which represents an inner-approximation of the non-convex feasible set of problem (24). The idea of our approach is to iteratively solve the optimization problem defined with this approximation.…”

“…The idea of our approach is to iteratively solve the optimization problem defined with this approximation. After each iteration, we refine the ICA of the feasible set in (24), and keep iterating until convergence to a stationary solution, as described next. The approximate optimization problem is defined as follows:…”