A simple soft linear detection for coded multi‐input multi‐output systems

Abstract

We propose a very simple and efficient soft linear multi‐input multi‐output (MIMO) detection scheme. The detection process is divided into two separate problems. The proposed scheme first detects MIMO symbols using conventional linear detection methods and produces soft bit information using a simple soft demapping method. Next, we refine the soft information by accounting for uneven post‐detection noise variance across MIMO layers. From the simulation result investigated in this paper, we first emphasize that powerful channel coding may suppress the differences of diversity gains among various MIMO detection schemes. This implies that the channel decoding operation may not be transparent to performance gain that resulted from MIMO detection process. The proposed scheme concentrates on accurate estimation of soft post‐MIMO detected information in a very simple manner, rather than concentrating on a complex MIMO detection scheme prior to decoding process. In combination with turbo codes, the proposed scheme produces comparable performance to maximum likelihood detection, even with the simplest scheme such as zero forcing detection, with drastically reduced complexity. Copyright © 2011 John Wiley & Sons, Ltd.

Efficient list‐sphere detection scheme for joint iterative multiple‐input multiple‐output detection

“…Compared with the STS method, the proposed method outperforms with (n IM , n ID ) of (1, 8), while it shows slightly worse performance with (n IM , n ID ) of (3,8). This is because the STS method performs a new search in each iteration by utilising a priori information provided by decoder.…”

“…In addition, the proposed method with channel-adaptive candidate lists produces slightly better BER performance than the non-adaptive LSD. Compared with the full search with (n IM , n ID ) of (1, 8), the proposed method with (n IM , n ID ) of (3,8) shows a power gain of more than 0.5 dB around the BER range of 10 −5 . The proposed method with (n IM , n ID ) of (3, 8) requires 20 × 3 = 60 SBI estimations, which is less than 25% of the 256 SBI estimations required for the full search with (n IM , n ID ) of (1, 8).…”

Complexity reduced soft bit estimation with iterative MMSE-SIC based MIMO detection

“…To reduce the exponential complexity of calculating (4), we adopt the concept of two sequential linear MIMO detection in [2]. Initially, with no a priori information available from the decoder at the first iteration, a simple MMSE detection without SIC is performed for symbol-wise detection followed by a soft bit extraction by using a simple linear method.…”

“…A main problem with the ML detector is its exponentially increasing complexity. In reference [2], a soft MIMO detection scheme with a linear order of complexity was proposed, by dividing the soft detection process into two sequential linear steps. However, its application was limited to noniterative MIMO systems.…”

Iterative Detection and Decoding of LDPC-Coded Multiuser Uplink Massive-MIMO Systems

“…MIMO 시스템의 간 섭 없는 신호를 검출하기 위한 선형 검출기로는 zero-forcing (ZF) 또는 minimum mean square error (MMSE) 검출기 등이 사용되어 왔다. Small-scale MIMO 시스템에 이러한 고전적 검출기와 터보 부호 를 연접한 수신기가 제안되었다 [3] . 이러한 고전적 검 출기들은 역행렬의 계산이 필요한데, massive-MIMO 그림 1.…”