Spatial Precoder Design for Space-Time Coded MIMO Systems: Based on Fixed Parameters of MIMO Channels
Tharaka A. Lamahewa, Rodney A. Kennedy, Thushara D. Abhayapala, Van K., Nguyen

TL;DR
This paper proposes linear spatial precoding schemes for MIMO systems that utilize fixed antenna placement parameters to enhance performance without requiring channel feedback, applicable to both coherent and non-coherent space-time coding.
Contribution
It introduces novel precoding schemes based on fixed antenna parameters, providing closed-form solutions for up to three receiver antennas and a generalized method for more.
Findings
Significant performance improvements at low SNRs for small antenna sizes.
Precoding schemes do not require channel state feedback.
Effective for both coherent and non-coherent space-time codes.
Abstract
In this paper, we introduce the novel use of linear spatial precoding based on fixed and known parameters of multiple-input multiple-output (MIMO) channels to improve the performance of space-time coded MIMO systems. We derive linear spatial precoding schemes for both coherent (channel is known at the receiver) and non-coherent (channel is un-known at the receiver) space-time coded MIMO systems. Antenna spacing and antenna placement (geometry) are considered as fixed parameters of MIMO channels, which are readily known at the transmitter. These precoding schemes exploit the antenna placement information at both ends of the MIMO channel to ameliorate the effect of non-ideal antenna placement on the performance of space-time coded systems. In these schemes, the precoder is fixed for given transmit and receive antenna configurations and transmitter does not require any feedback of channel…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Wireless Communication Techniques · Advanced MIMO Systems Optimization · Cooperative Communication and Network Coding
