Efficient Lattice-Reduction-Aided Successive Interference Cancellation for Clustered Multiuser MIMO System (original) (raw)

Optimal lattice-reduction aided successive interference cancellation for MIMO systems

2007

In this letter, we investigated the optimal minimummean-squared-error (MMSE) based successive interference cancellation (SIC) strategy designed for lattice-reduction aided multiple-input multiple-output (MIMO) detectors. For the sake of generating the MMSE-based MIMO symbol estimate at each SIC detection stage, we model the so-called effective symbols generated with the aid of lattice-reduction as joint Gaussian distributed random variables. However, after lattice-reduction, the effective symbols become correlated and exhibit a non-zero mean. Hence, we derive the optimal MMSE SIC detector, which updates the mean and variance of the effective symbols at each SIC detection stage. As a result, the proposed detector achieves a better performance compared to its counterpart dispensing with updating the mean and variance, and performs close to the maximum likelihood detector.

Interference cancellation assisted lattice-reduction aided detection for MIMO systems

2006

In this paper, we proposed and investigated the optimal successive interference cancellation (SIC) strategy designed for latticereduction aided multiple-input multiple-output (MIMO) detectors. For the sake of generating the optimal MIMO symbol estimate at each SIC detection stage, we model the so-called effective symbols generated with the aid of lattice-reduction as joint Gaussian distributed random variables. However, after lattice-reduction, the effective symbols become correlated and exhibit a non-zero mean. Hence, we derive the optimal minimum-mean-squared-error (MMSE) SIC detector, which updates the mean and variance of the effective symbols at each SIC detection stage. As a result, the proposed detector achieves an approximately 3 dB E b /N 0 gain and performs close to the maximum likelihood detector.

Lattice Reduction-Aided Successive Interference Cancellation for MIMO Interference Channels

IEEE Transactions on Vehicular Technology, 2014

In multiple-input-multiple-ouput (MIMO) interference channels (IFCs), interference alignment (IA) with zero-forcing (ZF) linear detection can be used to achieve the maximum degrees of freedom (DoFs). However, ZF linear detection usually degrades the performance due to the noise enhancement in practical systems. In this paper, we propose lattice reduction (LR)-aided successive interference cancelation (SIC) in conjunction with IA over lattice for three-user (and extendable to K-user) MIMO IFCs in which the interfering signals aligned over the lattices are detected and canceled rather than nulled out. To complete the proposed LR-aided SIC method, the detection ordering and the precoding matrix that minimize the mean square error are also determined.

A Diagonal Lattice Reduction Algorithm for MIMO Detection

IEEE Signal Processing Letters, 2000

Recently, an efficient lattice reduction method, called the effective LLL (ELLL) algorithm, was presented for the detection of multiinput multioutput (MIMO) systems. In this letter, a novel lattice reduction criterion, called diagonal reduction, is proposed. The diagonal reduction is weaker than the ELLL reduction, however, like the ELLL reduction, it has identical performance with the LLL reduction when applied for the sphere decoding and successive interference cancelation (SIC) decoding. It improves the efficiency of the ELLL algorithm by significantly reducing the size-reduction operations. Furthermore, we present a greedy column traverse strategy, which reduces the column swap operations in addition to the size-reduction operations.

A Comparison of Two Lattice-Reduction-Based Receivers for MIMO Systems

2008 IEEE Sarnoff Symposium, 2008

In this paper, we compare a new practical lattice reduction method, Seysen's algorithm, with the existing LLL lattice reduction approach. Seysen's algorithm considers all vectors in the lattice simultaneously and performs global search for lattice reduction, while the LLL algorithm concentrates on local optimization to produce a reduced lattice We also study their performance, when combined with linear detectors (Zero Forcing, MMSE and extended MMSE), and successive interference cancellation (SIC) detector. For MIMO digital communications, Seysen-based linear detectors achieve the same diversity order as the optimum ML detector. It outperforms the existing LLL-based linear detectors. Moreover, Seysen requires less computational time than the LLL scheme. However, this gap disappears in SIC scenario: Seysen-based SIC detector functions the same as LLL-based one, due to the efficiency of SIC itself.

Near-maximum-likelihood detection of MIMO systems using MMSE-based lattice reduction

2004

In recent publications the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In this paper, we adopt these lattice-reduction-aided schemes to the MMSE criterion. We show that an obvious way to do this is infeasible and propose an alternative method based on an extended system model, which in conjunction with simple successive interference cancellation nearly reaches the performance of maximum-likelihood detection. Furthermore, we demonstrate that a sorted QR decomposition can significantly reduce the computational effort associated with lattice-reduction. Thus, the new algorithm clearly outperforms existing methods with comparable complexity.

A Hybrid Method for Lattice-Reduction-Aided MIMO Detection

Proceedings of the 2nd World Congress on Electrical Engineering and Computer Systems and Science, 2016

Lattice reduction has been successfully applied to data detection in multiple-input multiple-output (MIMO) systems. In this paper, we introduce a polynomial time algorithm for lattice-reduction-aided (LR-aided) MIMO detection. The hybrid method we present integrates the length-based size reduction technique into an angle-measured method. To assess the performance of the algorithm, we compare it with the LLL algorithm, a widely used algorithm in MIMO and wireless communications. Our experimental results show that despite that the two algorithms have the same complexity, the hybrid method is empirically more efficient than the LLL algorithm, and the communication channels improved by our hybrid method have smaller bit error rate (BER) than those improved by the LLL algorithm in data detection.

SIC-Based Detection With List and Lattice Reduction for MIMO Channels

IEEE Transactions on Vehicular Technology, 2009

To derive low-complexity multiple-input-multiple-output (MIMO) detectors, we combine two complementary approaches, i.e., lattice reduction (LR) and list within the framework of the successive interference cancellation (SIC)-based detection. It is shown that the performance of the proposed detector, which is called the SIC-based detector with list and LR, can approach that of the maximum-likelihood (ML) detector with a short list length. For example, the signal-to-noise ratio (SNR) loss of the proposed detector, compared with that of the ML detector, is less than 1 dB for a 4 × 4 MIMO system with 16-state quadrature amplitude modulation (QAM) at a bit error rate (BER) of 10 −3 with a list length of 8.

MMSE-Based Lattice-Reduction for Near-ML Detection of MIMO Systems

Recently the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In this paper, we adopt these lattice-reduction aided schemes to the MMSE criterion. We show that an obvious way to do this is suboptimum and propose an alternative method based on an extended system model. In conjunction with simple successive interference cancellation this scheme almost reaches the performance of maximum-likelihood detection. Furthermore, we demonstrate that the application of Sorted QR Decomposition (SQRD) as a initialization step can significantly reduce the computational effort associated with lattice-reduction. Thus, the new algorithm clearly outperforms existing methods with comparable complexity.

VLSI implementation of a low-complexity LLL lattice reduction algorithm for MIMO detection

2010

Lattice-reduction (LR)-aided successive interference cancellation (SIC) is able to achieve close-to optimum error-rate performance for data detection in multiple-input multiple-output (MIMO) wireless communication systems. In this work, we propose a hardware-efficient VLSI architecture of the Lenstra-Lenstra-Lovász (LLL) LR algorithm for SIC-based data detection. For this purpose, we introduce various algorithmic modifications that enable an efficient hardware implementation. Comparisons with existing FPGA implementations show that our design outperforms state-of-the-art LR implementations in terms of hardware-efficiency and throughput. We finally provide reference ASIC implementation results for 130 nm CMOS technology.