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This paper proposes an adaptive candidate selection scheme in the QRM-MLD algorithm for MIMO detection. The QRM-MLD is a near-ML detection algorithm which can achieve a tradeoff between the BER performance and the computational complexity in the MIMO systems. In this paper, we adopt an adaptive candidate selection scheme into the QRM-MLD. First, similarly to the conventional QRM-MLD, the proposed...
This paper proposed a detection method combined the list detection with partial successive interference cancellation (SIC) based on the reciprocal lattice-reduction in MIMO system. List detection is an effective detection method for improving the performance of MIMO signal detection, but the computational expense depending on the list length is the bottleneck. To reduce the complexity of the list...
In this paper, we proposes a low-complexity lattice-reduction aided detection (LRAD) based on the Gram-Schmidt (GS) procedure in multi-input multi-output (MIMO) communications. The conventional LRAD achieves good bit error ratios (BERs) because it reduces the column vectors of the channel matrix close to orthogonal using LLL Algorithm. The proposed detection method reduces the column vectors of the...
The evaluation of garbage collection (GC) algorithms typically needs a complicated experimental phase, involving a considerable amount of engineering effort. This paper presents a new evaluation method to simplify this experimental phase. By the hypothesis that most of the GC algorithms are based on analyzing a set of object graphs, we propose an indirect evaluation approach that only focuses on the...
Lattice reduction is an effective technique for improving the performance of MIMO data detection. In this paper, we analyze lattice reduction processing on the basis lattice and the dual lattice for MIMO detection and investigate the parameters which affect the complexity of the LLL algorithm. Through use of the dual lattice in the LLL algorithm, the BER performances are improved about 2.2dB at BER=10...
To the best of our knowledge, the problem of mining multi-relational frequent patterns in data streams is still unsolved up to now. To attack this problem, an algorithm RFPS, which is based on novel data synopsis and declarative bias, is proposed in this paper. By introducing a new data synopsis method, where period sampling is used, many samplespsila checking operations are avoided. Meanwhile, lots...
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