Low latency group‐sorted QR decomposition algorithm for larger‐scale MIMO systems

Abstract

Sorted QR decomposition (SQRD) has been extensively adopted for various multiple-input-multiple-output (MIMO) detectors, in which the sorting process incurs severe latency when it comes to larger-scale MIMO situations. This paper proposes a group-SQRD (GSQRD) algorithm to alleviate the latency problem of general SQRD architectures for larger-scale MIMO systems. Via predictively sorting a group of 4 columns at one stage, the GSQRD could eliminate the processing latency by 41% for decomposing 16 ×16 complex-valued matrices. Additionally, this percentage even rises up to 68% for decomposing 128 ×128 matrices. To analyse the side effects, the GSQRD is applied in various MIMO detectors in a simulation link, which exhibits a negligible performance degradation for MIMO detection. Moreover, GSQRD is a hardware-friendly algorithm because the division and square root operations in GSQRD are converted to multiplications for simplifying the hardware implementation. Based on this algorithm, two corresponding hardware architectures, which contains 2 and 4 columns respectively in a sorting group, are also implemented with 65-nm CMOS technology. These architectures can work at 513 MHz to decompose 16 ×16 complex-valued matrices. The processing latencies are respectively 0.32 and 0.26 μs, superior to the state-of-art designs.