@article{li_rupasinghe_bursalioglu_wang_papadopoulos_caire_2017, title={Directional Training and Fast Sector-based Processing Schemes for mmWave Channels}, ISSN={["1550-3607"]}, DOI={10.1109/icc.2017.7997050}, abstractNote={We consider a single-cell scenario involving a single base station (BS) with a massive array serving multi-antenna terminals in the downlink of a mmWave channel. We present a class of multiuser MIMO schemes, which rely on uplink training from the user terminals, and on uplink/downlink channel reciprocity. The BS employs virtual sector-based processing according to which, user-channel estimation and data transmission are performed in parallel over non-overlapping angular sectors. The uplink training schemes we consider are non-orthogonal, that is, we allow multiple users to transmit pilots on the same pilot dimension (thereby potentially interfering with one another). Elementary processing allows each sector to determine the subset of user channels that can be resolved on the sector (effectively pilot contamination free) and, thus, the subset of users that can be served by the sector. This allows resolving multiple users on the same pilot dimension at different sectors, thereby increasing the overall multiplexing gains of the system. Our analysis and simulations reveal that, by using appropriately designed directional training beams at the user terminals, the sector-based transmission schemes we present can yield substantial spatial multiplexing and ergodic user-rates improvements with respect to their orthogonal-training counterparts.}, journal={2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC)}, author={Li, Zheda and Rupasinghe, Nadisanka and Bursalioglu, Ozgun Y. and Wang, Chenwei and Papadopoulos, Haralabos and Caire, Giuseppe}, year={2017} } @article{iscar_guvenc_dikmese_rupasinghe_2018, title={Efficient Noise Variance Estimation Under Pilot Contamination for Massive MIMO Systems}, volume={67}, ISSN={["1939-9359"]}, url={https://doi.org/10.1109/TVT.2017.2766226}, DOI={10.1109/tvt.2017.2766226}, abstractNote={Massive multiple input multiple output (MIMO) is expected to be one of the enabling technologies for fifth-generation cellular networks. One of the major challenges in massive MIMO systems is the accurate joint estimation of the channel and noise variance, which significantly affects the performance of wireless communications in practical scenarios. In this paper, we first derive a novel maximum likelihood estimator for the noise variance at the receiver of massive MIMO systems considering practical impairments such as pilot contamination. Then, this estimate is used to compute the minimum mean square error estimate of the channel. In order to measure the performance of the proposed noise variance estimator, we derive the corresponding Cramér–Rao lower bound (CRLB). Simulation results show that the estimator is efficient in certain scenarios, outperforming existing approaches in the literature. Furthermore, we develop the estimator and the CRLB for equal and different noise variance at the receive antennas. Although the proposed estimator is valid for all antenna array sizes, its use is particularly effective for massive MIMO systems.}, number={4}, journal={IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Iscar, Jorge and Guvenc, Ismail and Dikmese, Sener and Rupasinghe, Nadisanka}, year={2018}, month={Apr}, pages={2982–2996} }