LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Performance Analysis of Downlink Linear Precoding in Massive MIMO Systems Under Imperfect CSI

Photo from wikipedia

Demands of wireless data traffic, throughput, the number of wireless mobile connections and devices will always increase. In addition, the concern about energy consumption is also growing for wireless communication… Click to show full abstract

Demands of wireless data traffic, throughput, the number of wireless mobile connections and devices will always increase. In addition, the concern about energy consumption is also growing for wireless communication systems. Massive MIMO system is a new emerging research area to resolve these issues. In this paper, the performance of Massive MIMO downlink including linear precoding is evaluated. Spectral efficiency through achievable rate and energy efficiency through transmit power of ZF and MRT linear precoding is investigated under practical limitations, such as imperfect CSI, less complexity processing and inter user interference. Since ZF and MRT precoding can balance the system performance and complexity. Different channel estimation values are considered in order to compare the performance of these precoding techniques in the given system. The achievable rate and the downlink transmit power of ZF and MRT precoding techniques are derived, analyzed and compared under the same conditions and assumptions. Several scenarios are considered to investigate these performance parameters. It is found that when the ratio of BS antennas and number of users is large, ZF is better than MRT while when the ratio is quite small it makes MRT better than ZF for the same conditions.

Keywords: linear precoding; mrt; massive mimo; performance; imperfect csi

Journal Title: Wireless Personal Communications
Year Published: 2017

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.