Are all basis updates for lattice-reduction-aided MIMO detection necessary? (original) (raw)
Related papers
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.
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.
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.
2010
Lattice reduction-aided linear detectors for MIMO systems are a promising receiver structure for low-complexity implementations. In this paper we present a lattice reductionaided MIMO data detection architecture based on Seysen's algorithm, where the algorithm is carried out exclusively on the Gram matrix of the channel and its inverse. Furthermore, we describe and evaluate several modification of Seysen's algorithm tailored to reduce the total complexity with respect to hardware implementation. By means of complexity-performance trade-offs we demonstrate the potential benefit of the various algorithmic modifications. First, novel schemes to identify the update steps in each iteration of Seysen's algorithm are presented. Second, we show that further complexity reduction of Seysen's algorithm can be obtained by severely constraining the update coefficients. Eventually, methods are devised that terminate Seysen's algorithm prematurely and thus result in a reduction of the average complexity.
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 the robustness of lattice-reduction aided detectors in correlated MIMO systems
IEEE 60th Vehicular Technology Conference, 2004. VTC2004-Fall. 2004, 2000
Recently the use of lattice-reduction for signal detection in multiple antenna systems has been proposed. In combination with simple successive interference cancellation this scheme achieves near maximum-likelihood performance. To this end, the given MIMO channel is transformed into an almost orthogonal matrix leading to less noise enhancement within the detection. In this paper, we investigate the performance of common and lattice-reduction-aided detection schemes for correlated fading channels. We show, that the new scheme achieves significant gain in comparison to common algorithms. Thus, the new algorithm clearly outperforms existing methods with comparable complexity and is also more robust with respect to spatial correlation.
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.
A low complexity ZF-based lattice reduction detection using curtailment parameter in MIMO systems
2016
As the large-scale multiple-input multiple-output (MIMO) systems have been advanced in wireless communication, the low complexity and high performance receiver technique have been required. Recently, lattice reduction technique have attracted attention in MIMO detection. Especially, lattice reduction aided linear detection like zero-forcing (ZF) can largely improve the performance with low complexity. Among all the lattice reduction algorithms, the Lenstra-Lenstra-Lovasz (LLL) algorithm is well-known and widely used algorithm. LLL algorithm reduces the basis of channel matrix by using two conditions and it adopts a parameter in order to get nearly orthogonal basis. Although the parameter is defined range, a constant value is commonly used. However it can't be said that the constant value is the best value for all MIMO system. In this paper, we propose an appropriate parameter to reduce computational complexity in LLL algorithm for ZF detection and we also propose an architecture to adapt our proposed parameter in MIMO detection. The proposed parameter is showed simply and corresponds to the number of antennas. Simulation results show that the proposed parameter provides LLL lattice reduction aided ZF detection achieving the same performance as the widely used constant value with lower complexity and also correspond to every MIMO system including large-scale MIMO system.
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.