Recently, large-scale or massive multiple-input multiple-output (MIMO) techniques have been proposed to dramatically improve the performance of wireless networks. Massive MIMO base stations are equipped with a large number of antennas, co-located or distributed around the main base station site, so as to mitigate the effects of noise, fading, and multi-user interference. The key enabler lies in the asymptotic orthogonality properties of the large-dimensional random vectors associated with the massive MIMO channels, and in the large array gains that massive MIMO arrays offer. Additional promises of large-scale antenna systems include (i) lending themselves to low-complexity precoding/detection, (ii) savings in terms of radiated RF energy per transmitted information bit, (iii) enabling hardware-friendly waveform shaping, and (iv) reduced sensitivity to distortions stemming from hardware non-linearities and imperfections. Yet, challenges abound regarding both fundamental performance analysis as well as implementation of massive MIMO systems in real-life scenarios. To foster understanding within this hot topic, original contributions are sought in the following areas: Channel estimation for massive MIMO systems Low-complexity precoding and decoding design for massive MIMO systems Energy-efficient signal processing for massive MIMO systems Impact and mitigation of hardware impairments in massive MIMO systems Resource allocation schemes for massive MIMO systems Distributed large-scale MIMO systems Network optimization for massive MIMO systems, deployment scenarios Experiments and measurements for massive MIMO channels Efficient feedback methods for FDD deployments