Evaluation of an Antenna Selection Strategy for Reduced Massive MIMO Complexity

Abstract

Mobile connectivity has become not only essential but a necessity for many network users. The number of mobile subscribers is growing rapidly and the demand for more bandwidth and higher data rates continues to increase (CISCO Global Cloud Index (GCI), 2018). To support this demand, 5G systems promise to deliver a major paradigm shift with respect to previous wireless communication systems using new technologies such as Massive MIMO (Andrews et al., 2014;Larsson et al., 2014). MIMO technology has been a breakthrough for wireless communication systems in terms of increased reliability and higher data throughput and it is imagined that more benefits could be harvested from scaled-up versions (Rusek et al., 2013).In Marzetta (2010), the author introduced the concept of Massive MIMO and demonstrated that an excessive number of radiating elements (M) at the transmitting side paired with a number of active users (K) permits the use of simple linear precoders and increases the overall spectrum efficiency. In Björnson et al. (2016), Lu et al. (2014), Ngo et al. (2013), Rusek et al. (2013, an overview of Massive MIMO technology is thoroughly presented alongside its main advantages and challenges. Massive MIMO systems can eliminate the effects of small-scale fading and uncorrelated noise thus reducing intercell interference. As a result, the corresponding channel is formed by a set of nearly perfect orthogonal subchannels (Narasimhan & Chockalingam, 2014). Even though MIMO systems are already operating worldwide, largescale MIMO has only been tested in labs (

Hardware Efficient Massive MIMO Systems with Optimal Antenna Selection

“…The number of antennas to be chosen is determined by adjusting an appropriate amount of transmit power to be radiated during the selection process. The number of antenna elements to be selected accounts for the system complexity [27][28][29].…”