In order to evaluate the performance of new mobile network technologies, system level simulations are crucial. They aim at determining whether, and at which level predicted link level gains impact network performance. In this paper we present a MATLAB computationally efficient LTE system level simulator. The simulator is offered for free under an academic, noncommercial use license, a first to the authors' knowledge. The simulator is capable of evaluating the performance of the Downlink Shared Channel of LTE SISO and MIMO networks using Open Loop Spatial Multiplexing and Transmission Diversity transmit modes. The physical layer model is based on the postequalization SINR and provides the simulation pre-calculated "fading parameters" representing each of the individual interference terms. This structure allows the fading parameters to be pregenerated offline, vastly reducing computational complexity at run-time.

In this article, we introduce MATLAB-based link and system level simulation environments for UMTS Long-Term Evolution (LTE). The source codes of both simulators are available under an academic non-commercial use license, allowing researchers full access to standard-compliant simulation environments. Owing to the open source availability, the simulators enable reproducible research in wireless communications and comparison of novel algorithms. In this study, we explain how link and system level simulations are connected and show how the link level simulator serves as a reference to design the system level simulator. We compare the accuracy of the PHY modeling at system level by means of simulations performed both with bit-accurate link level simulations and PHY-model-based system level simulations. We highlight some of the currently most interesting research questions for LTE, and explain by some research examples how our simulators can be applied.

No abstract

In this paper, we present an Approximate Linear Minimum Mean Square Error (ALMMSE) fast fading channel estimator for Orthogonal Frequency Division Multiplexing (OFDM). The ALMMSE channel estimator utilizes the knowledge of the structure of the autocorrelation matrix given by the Kronecker product between the time correlation matrix and the frequency correlation matrix. We separate the Linear Minimum Mean Square Error (LMMSE) filtering matrix into two matrices corresponding to individual filtering in frequency and time. The eigenvalues of these two matrices are rank-one approximated by the eigenvalues of the LMMSE filtering matrix. The complexity of the ALMMSE estimator can be scaled by varying the number of the considered number of eigenvalues. Simulation results show that the proposed ALMMSE channel estimator looses only 0.1 dB compared to the LMMSE channel estimator in realistic scenarios.

Inter-cell Interference (ICI) is a key issue in Orthogonal Frequency-Division Multiple Access (OFDMA) systems.Since OFDMA was proposed to be used in next generation networks several schemes have been investigated for mitigating the ICI. One of the techniques that promises improvement in reducing ICI is Partial Frequency Reuse (PFR). In this paper we investigate a Flexible Bandwidth Allocation (FBA) scheme for PFR depending on the network-load, which allocates bandwidth dynamically in the network. The scheme is based on the assumption that a cell is not loaded homogeneously. We develop a suitable network description to obtain the optimum PFR zone partitioning as a function of the dynamic bandwidth allocation. Thus, our paper presents a general framework for intelligent frequency planning in wireless networks. Compared to simpler PFR schemes, our simulation results show that the cell capacity for reuse-1 can be increased by 2 b/s/Hz when our scheme is used by exploiting the inhomogeneities in the load.