Efficiently using extrinsic gain for candidate vectors selection in QR-LRL based IDD MIMO receiver
24 Dec 2012-pp 221-224
TL;DR: Simulation results shows that significant performance improvement is achieved while keeping the receiver design simple, and decision is made to update candidate vector set for soft output generation.
Abstract: Various OSIC MIMO detectors are considered suboptimal in terms of performance and complexity, however suffers from error propagation. QR-LRL is considered to be most effective to mitigate error performance as it detects the least reliable layer(LRL) symbol first. It achieves hard ML performance, but suffers from empty vector set(EVS) problem for soft output generation. Some of the previous work mitigates this problem effectively and achieves soft ML performance at the cost of complexity. QR-LRL based IDD(Iterative Detection and Decoding) is an alternative solution, which exchanges the extrinsic information between detector and decoder. Based on feed back knowledge from decoder, decision is made to update candidate vector set for soft output generation. Simulation results shows that significant performance improvement is achieved while keeping the receiver design simple.
Citations
More filters
01 Oct 2014
TL;DR: An enlargement of candidate vector set of QR-LRL based MIMO detector for efficient soft output generation is proposed in this article, which effectively removes EVS problem and achieves soft output ML performance while keeping the computation complexity low, especially at low modulation order.
Abstract: An enlargement of candidate vector set of QR-LRL (QR — Least Reliable Layer) based MIMO detector for efficient soft output generation is proposed. Previous work [8] shows that QR-LRL based MIMO detector approaches hard decision output ML performance, but does not match the soft output ML performance due to empty candidate vector set problem. Performance degradation is more severe when modulation order is low. Some of the previous methods have provided solutions to mitigate Empty Vector Set (EVS) problem [4] [8] [9], but are not efficient in terms of performance or computation complexity. In this paper, we enlarged candidate vector set of QR-LRL detector by applying every constellation point at each layer. The proposed detector thus effectively removes EVS problem and achieves soft ML performance while keeping the computation complexity low, especially at low modulation order.
5 citations
Cites methods from "Efficiently using extrinsic gain fo..."
...Author[11] lessen the EVS problem by jointly using MIMO detector with TURBO extrinsic decoder in decision feedback mode....
[...]
27 Apr 2015
TL;DR: A Multi-user Multiple-Input Multiple-Output (MU-MIMO) based Cognitive Radio network where the unlicensed secondary uses (SU) can simultaneously use the spectrum which is used by a licensed primary user (PU) has been cancelled.
Abstract: In this paper, we propose a Multi-user Multiple-Input Multiple-Output (MU-MIMO) based Cognitive Radio network where the unlicensed secondary uses (SU) can simultaneously use the spectrum which is used by a licensed primary user (PU). The interference caused by the secondary user to the primary user has been cancelled. This is done by using Block Diagonalization (BD) followed by QR-MRL in order to cancel the interference caused by PU antennas. Previous works, such as ZF (Zero Forcing)-BD and MMSE (Minimum Mean Squared Error)-BD are succeed to cancel the interference among multiple users. Here, the performance comparison has been made in terms of Bit Error Rate (BER) plots for ZF-BD, MMSE-BD and QR-MRL-BD. Also, these techniques have been compared with BER plot obtained when SUs interfere with the PUs. The results show that the BD method is able to cancel the interference caused by the SUs successfully and the QR-MRL method which is an ordered successive interference cancellation(OSIC) method effectively cancels the interference caused among user's antennas. A significant improvement in BER plot for QR-MRL-BD is observed. Also, a simulink model for ZF-BD has been discussed for future hardware implementation.
4 citations
Cites background from "Efficiently using extrinsic gain fo..."
...Although Zero forcing (ZF) and Minimum mean squared error (MMSE) detectors are not complex but their performances are poor....
[...]
01 Jan 2015
TL;DR: Simulation results showed that the proposed technique confirms improved detection compared to the conventional methods for multiuser scenario.
Abstract: QR-Least reliable layer (QR-LRL) technique in fusion with the channel block diagonalization (BD) is proposed for signal detection in the multiuser multiple input and multiple output (MU-MIMO) system. Literature survey shows various precoding techniques like BD-ZF, BD-MMSE, dirty paper coding (DPC) to overcome multiuser interference. However, they suffer in the terms of either noise enhancement or complexity or sum rate capacity. It is also shown in the literature that QR-LRL, an ordered successive interference cancellation (OSIC) detector achieves hard/soft ML performance with low complexity for SM-MIMO systems. In this paper, BD and QR-LRL are associated together in order to enhance the signal detection for MU-MIMO system. Simulation results showed that the proposed technique confirms improved detection compared to the conventional methods for multiuser scenario.
1 citations
Cites methods from "Efficiently using extrinsic gain fo..."
...The OSIC detector has gone through an endless research lately [3-4, 7-12]....
[...]
References
More filters
TL;DR: An improved vertical Bell Labs layered space-time (V-BLAST) receiver which takes the decision errors into account is introduced and an iterative detection and decoding (IDD) scheme for coded layeredspace-time architectures in MIMO-OFDM systems is proposed.
Abstract: Multiple-input-multiple-output (MIMO) systems provide a very promising means to increase the spectral efficiency for wireless systems. By using orthogonal frequency-division multiplexing (OFDM), wideband transmission can be achieved over frequency-selective fading radio channels. First, in this paper, we introduce an improved vertical Bell Labs layered space-time (V-BLAST) receiver which takes the decision errors into account. Second, we propose an iterative detection and decoding (IDD) scheme for coded layered space-time architectures in MIMO-OFDM systems. For the iterative process, a low-complexity demapper is developed by making use of both nonlinear interference cancellation and linear minimum mean-square error filtering. Also, a simple cancellation method based on hard decision is presented to reduce the overall complexity. Simulation results demonstrate that the proposed IDD scheme combined with the improved V-BLAST performs almost as well as the optimal turbo-MIMO approach, while providing tremendous savings in computational complexity.
197 citations
27 Nov 2000
TL;DR: It is shown that iterative detection and decoding (IDD) can significantly improve the performance of coded BLAST and may in fact reduce the overall receiver complexity.
Abstract: In BLAST (Bell Labs' Layered Space Time) systems, very high spectral efficiency can be achieved by employing antenna arrays at both transmit and receive sides. Coding for these array systems is an interesting topic, as such, has seen intensive research. We study coding architectures constructed from conventional codes including convolutional codes and Reed Solomon codes. Our main interest is in the performance and complexity trade-offs involved in the design of coding/decoding and signal detection algorithms. We show that iterative detection and decoding (IDD) can significantly improve the performance of coded BLAST. In some cases, IDD allows for very simple detection algorithms to be used at the receiver front end. Therefore, it may in fact reduce the overall receiver complexity. Our results again demonstrate that coded V-BLAST (vertical-BLAST) is a promising architecture to achieve the great potential of BLAST with limited complexity.
125 citations
11 Dec 2006
TL;DR: This paper proposes the use of a combination of linear MMSE and soft successive interference cancellation based detectors for the application in (turbo-)MIMO receivers and shows that for a number of scenarios, both techniques show performance close to that of more sophisticated detection techniques, at a fraction of the complexity.
Abstract: In this paper, we propose the use of a combination of linear MMSE and soft successive interference cancellation based detectors for the application in (Turbo-)MIMO receivers. In an adaptive setup we switch between the two detector types based on the quality of the received signal, while in a hybrid setup, we use a linear MMSE in the first and a SoftSIC in all subsequent iterations. We show that for a number of scenarios, both techniques show performance close to that of more sophisticated detection techniques, at a fraction of the complexity.
31 citations
"Efficiently using extrinsic gain fo..." refers background or methods in this paper
...Error propagation can be minimized by effectively using SIC detector with IDD....
[...]
...IDD receiver....
[...]
...Proposed decision feedback IDD for mitigating EVS using extrinsic gain of Turbo decoder is described below....
[...]
...Various solution for reducing error propagation are described in[4][6]....
[...]
...In[4] author used MMSE-IDD(Minimum Mean Square Error), SIC-IDD in adaptive and hybrid way to gain maximum throughput depending on the receiving signal quality....
[...]
TL;DR: It is shown that the selection of the first layer impacts the error performance significantly, and based on the observation, a novel signal detection method QR-LRL is proposed, which is shown to be the best choice in terms of noise enhancement in detecting the other layers.
Abstract: The performance of the ordered successive interference cancellation (OSIC) signal detection method is well known to depend on the successful detection of the first layer. In a previous work, in an effort to mitigate the error propagation effect, all the constellation points were tried as the first layer symbol, thereby achieving a better performance. In this letter, we show that the selection of the first layer impacts the error performance significantly, and based on the observation, we propose a novel signal detection method QR-LRL. In the proposed work, the least reliable layer (LRL) is chosen to be the first layer, which is shown to be the best choice in terms of noise enhancement in detecting the other layers. Also, we discuss Log Likelihood Ratio (LLR) computation when the proposed method is used. Computer simulations confirm the efficacy of the proposed method.
31 citations
TL;DR: A novel detection method is proposed which can generate reliable soft-outputs while avoiding the empty vector set problem and efficiently uses the upper triangular structure in QR decomposition.
Abstract: A simple detector named QR-LRL for MIMO systems was proposed in [7] and it was shown that QR-LRL approached the hard-output ML performance. However, its soft-output performance is not capable of approaching the near ML performance. In this letter, we propose a novel detection method which can generate reliable soft-outputs while avoiding the empty vector set problem. The proposed detector efficiently uses the upper triangular structure in QR decomposition. Simulation results show that the proposed detector can approach the near soft-output ML performance as well as hard-output with feasible complexity.
9 citations