In this paper, a new stochastic channel model (SCM) is proposed for fifth-generation (5G) systems. By means of the sum-of-sinusoids (SoS) method to generate spatially consistent random variables (SCRVs), the proposed model extends the 3rd Generation Partnership Project (3GPP)-SCM by considering three important features for accurate simulations in 5G, i.e., support for dual mobility, spatial correlation at both ends of the link and considerable reductions of the required memory consumption when compared with existing models. A typical problem presented in existing channel models, namely the generation of uncorrelated large scale parameters (LSPs) and small scale parameters (SSPs) for close base stations (BSs), is solved, then allowing for more realistic numerical evaluations in most of the 5G scenarios characterized by a large density of BSs and user equipments (UEs) per unit of area, such as ultra-dense networks (UDNs), indoor environments, device-to-device (D2D) and vehicular-to-vehicular (V2V). The proposed model emerges as the first SCM, and therein lower complexity when compared with ray-tracing (RT)based models, that comprises all the following features: support for single and dual mobility with spatial consistency, smooth time evolution, dynamic modeling, large antenna array, frequency range up 100 GHz and bandwidth up to 2 GHz. Some of the features are calibrated for single mobility in selected scenarios and have shown a good agreement with the calibration results found in the literature.

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Abstract-In this letter we present a new approach for non-linear interference cancellation detectors allowing all layers of a generic layered space-time multiplexing scheme to achieve an improved diversity order at the receiver which enhances its performance as a whole. This goal is achieved by adding a backward recursion in traditional non-linear interference cancellation detectors, e.g. successive interference cancellation (SIC) and ordered successive interference cancellation (OSIC). Our illustrative results confirm that by using this simple detection approach, all layers of a generic layered space-time multiplexing scheme achieve an improved diversity gain at the receiver. IndexTerms-Multiple antenna systems, successive interference cancellation (SIC), backward recursion

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In this paper we propose a pilot-based OFDM channel estimator based on the combination of low-pass filtering and delay-subspace projection. The proposed estimator, which we abbreviate ST-LP, is robust in the sense it does not require prior statistical knowledge of the channel. The only assumptions are the least-square (LS) estimates have limited spectrum and the channel follows the tapped delay line (TDL) model, which are commonly taken in practice. Since it is desirable slow delay variations operability acceptance, the delay-subspace is tracked by a subspace tracking (ST) algorithm. The ST-LP estimator can be implemented by two filtering structures, which provide a trade-off between accuracy and complexity. Simulation results confirm the superior performance of the ST-LP estimator when compared to methods already reported in the literature.