• Title/Summary/Keyword: simplified matrix-vector multiplication

Search Result 2, Processing Time 0.014 seconds

Design of Low Complexity and High Throughput Encoder for Structured LDPC Codes (구조적 LDPC 부호의 저복잡도 및 고속 부호화기 설계)

  • Jung, Yong-Min;Jung, Yun-Ho;Kim, Jae-Seok
    • Journal of the Institute of Electronics Engineers of Korea SD
    • /
    • v.46 no.10
    • /
    • pp.61-69
    • /
    • 2009
  • This paper presents the design results of a low complexity and high throughput LDPC encoder structure. In order to solve the high complexity problem of the LDPC encoder, a simplified matrix-vector multiplier is proposed instead of the conventional complex matrix-vector multiplier. The proposed encoder also adopts a partially parallel structure and performs column-wise operations in matrix-vector multiplication to achieve high throughput. Implementation results show that the proposed architecture reduces the number of logic gates and memory elements by 37.4% and 56.7%, compared with existing five-stage pipelined architecture. The proposed encoder also supports 800Mbps throughput at 40MHz clock frequency which is improved about three times more than the existing architecture.

$S^{2}MMSE$ Precoding for Multiuser MIMO Broadcast Channels (다중 사용자 MIMO 방송 채널을 위한 $S^{2}MMSE$ 프리코딩)

  • Lee, Min;Oh, Seong-Keun
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.33 no.12A
    • /
    • pp.1185-1190
    • /
    • 2008
  • In this paper, we propose an simplified successive minimum mean square error ($S^{2}MMSE$) algorithm that can simplify the computational complexity for precoding matrix generation in the successive minimum mean square error (SMMSE) precoding method, which is adopted as a multiuser multiple-input multiple-output (MU-MIMO) precoding technique in the IST (information society technologies)-WINNER (wireless world initiative new radio) project. The original algorithm generates the precoding matrix by calculating all individual precoding vectors with each requiring its own MMSE nulling matrix, over all receive antennas for all users. In contrast, this proposed algorithm first calculates the MMSE nulling matrix for each user, and then calculates all precoding vectors for respective receive antennas of the corresponding user by using the identical MMSE nulling matrix, in which only a simple matrix-vector multiplication is required for each vector. Consequently, it can simplify significantly the computational complexity to generate a precoding matrix for SMMSE precoding.