Guided Search MIMO Detectors Aided by Lattice Reduction (original) (raw)

Guided Search MIMO Detectors aided by Lattice Reduction under Correlated Channels

IEEE Latin America Transactions, 2015

Under MIMO channels, the matched filter detection becomes inefficient to deal with high data throughput demanding systems. The performance or system capacity under conventional detection will be substantially degraded when the spatial diversity provided by multiple antennas can not be fully exploited and the detection process is unable to efficiently separate the signal from each antenna. The solution discussed in this paper seeks to establish more efficient detectors for MIMO systems with the aid of the lattice reduction (LR) technique. These detectors use information from the interfering signals in a way to improve the signal detection in the antenna of interest, thus providing advantages over the conventional system, at the expense of increasing complexity. The focus of this paper consists in comparing the characteristics of three representative sub-optimal detectors based on the maximum-likelihood function as well as on the guided search principle, previously analyzed in [1]. In this way, the complexity × performance trade-off for the sphere detector (SD), the QR decomposition-based detector (QRD) the greedy search detector (GSD) and its variants, all of them aided (or not) by the LR technique are analyzed and its potential of use in MIMO systems is put in perspective.

Hybrid Guided Search Detector for MIMO Systems

In multiple-input-multiple-output (MIMO) systems, there is a performance degradation using conventional detector (CD) due to the combined effects of the signal interference between antennas and the possible correlation between the received fading signals. Thus, the matched filter in each received antenna becomes inefficient in high data throughput demanding systems. The performance or system capacity under conventional detection will be substantially degraded when the spatial diversity provided by multiple antennas can not be fully exploited and the detection process is unable to efficiently separate the signal from each antenna. The solution discussed in this paper seeks to establish more efficient detectors for MIMO systems. These detectors use information from the interfering signals in a way to improve the signal detection in the antenna of interest, thus providing advantages over the conventional system, at the expense of increasing complexity. The focus of this paper consists in proposing a hybrid guided search MIMO detector utilizing the main advantages of two representative sub-optimal detectors based on the maximum-likelihood function and the guided search principle, the Sphere Detector (SD) and the QR decomposition with M algorithm based (QRD-M).

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.

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.

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 Conditional Detection for MIMO Systems

IEEE Transactions on Communications, 2014

We introduce a low-complexity detector with nearoptimal performance for transmission over multi-antenna systems. By using lattice basis reduction for generating almost orthogonal channel submatrices, we enhance the conditional optimization technique to implement a fast yet efficient detector. The lattice-reduction-aided (LRA) conditional method is presented as a general detection technique over fading channels to yield significant saving in computational complexity while achieving close to Maximum Likelihood (ML) error performance. By employing the orthogonality defect factor as a universal measure to select a near-orthogonal channel submatrix for conditional detection, we implement efficient detectors for MIMO systems. In particular, an almost optimal decoder with linear complexity for the Golden code is presented over quasi-static channels.

On Decreasing the Complexity of Lattice-Reduction-Aided K-Best MIMO Detectors

2009

The application of Lattice Reduction techniques over the MIMO channel matrix is known to improve the performance of MIMO detectors. Several authors have proposed Lattice-Reduction-Aided K-Best detectors for improving the performance of conventional K-Best algorithms. In this paper, efficient ways of decreasing the computational complexity of previously proposed schemes are presented. The knowledge about how the Lattice Reduction stage affects the transmitted symbols is exploited in order to significantly decrease the complexity without performance loss.

Channel-adaptive complex K-best MIMO detection using lattice reduction

2014 IEEE Workshop on Signal Processing Systems (SiPS), 2014

Lattice reduction (LR) aided detectors mitigate the exponentially increasing complexity of large multiple-input, multiple-output (MIMO) systems while achieving near-optimal performance with low computational complexity. In this paper, a channel-adaptive complex-domain LR-aided K-best MIMO detector is presented that reduces the gap between the K-best sphere decoding (SD) detector and the maximum likelihood (ML) optimal MIMO detector. While maintaining BER performance, computational complexity is reduced by 50% over a conventional complex domain K-best SD detector by implementing a new ondemand complex-domain candidate symbol selection algorithm. Two tunable variables in the candidate selection process are introduced to enable both coarse-grained and fine-grained adaptation of computational complexity to channel conditions.

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.