Near maximum likelihood block signal detection using QR decomposition and m-algorithm (QRm-mLBD) can improve a bit error rate (BER) performance of cyclic prefix inserted single-carrier (CP-SC) transmissions. However, ...
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ISBN:
(纸本)9781467320542;9781467320528
Near maximum likelihood block signal detection using QR decomposition and m-algorithm (QRm-mLBD) can improve a bit error rate (BER) performance of cyclic prefix inserted single-carrier (CP-SC) transmissions. However, it requires a fairly large number m of surviving paths in the m-algorithm and leads to very high computational complexity. Replacing the CP by training sequence (TS) was shown to reduce the number of m. Another approach to reduce the complexity of QRm-mLBD is to modify the tree structure constructed by QR decomposition for mL detection. Recently, we proposed a 2-step QRm-mLBD which prunes unreliable symbol candidates before tree search by using the minimummean square error based frequency-domain equalization (mmSE-FDE) output. In this paper, we apply the 2-step QRm-mLBD to TS inserted SC (TS-SC) transmission in order to further reduce the complexity of QRm-mLBD. We show by computer simulation that 2-step QRm-mLBD can reduce the complexity compared to conventional QRm-mLBD while keeping almost the same BER performance.
2-step maximum likelihood block signal detection employing QR decomposition and m-algorithm (QRm-mLBD) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission while reducing ...
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ISBN:
(纸本)9781467309905;9781467309882
2-step maximum likelihood block signal detection employing QR decomposition and m-algorithm (QRm-mLBD) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission while reducing the computational complexity compared to maximum likelihood detection (mLD). In 2-step QRm-mLBD, unreliable symbol candidates are removed by performing minimummean square error based frequency-domain equalization (mmSE-FDE) prior to QRm-mLBD. However, a large number m of surviving paths is still required in the m-algorithm to achieve a BER performance close to the matched filter (mF) bound. In this paper, to remedy this problem, we introduce a detection ordering to 2-step QRm-mLBD. We will show by computer simulation that the use of detection ordering can achieve the same BER performance as 2-step QRm-mLBD while reducing the computational complexity.
The m-algorithm is a reduced complexity, breadth-first, trellis search alternative to the Viterbi algorithm. It is particularly useful when the number of trellis states is so large as to render Viterbi detection impra...
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The m-algorithm is a reduced complexity, breadth-first, trellis search alternative to the Viterbi algorithm. It is particularly useful when the number of trellis states is so large as to render Viterbi detection impractical. When dealing with complex or long target responses, values of m >= 16 may be required in order to approach mLD performance. Performing path selection for m >= 16 using previously reported methods can be computationally complex and prohibitive to practical hardware implementation. This paper details reduced complexity path selection networks for use with large values of m. A strategy for the construction of reduced complexity networks is presented and can be used to create networks for a variety of values of m and for other applications where m-algorithm detection can be employed. The use of these networks will allow for practical realisable hardware implementations of m-algorithm detectors for m >= 16.
2-step maximum likelihood block signal detection employing QR decomposition and m-algorithm (QRm-mLBD) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission while reducing ...
详细信息
ISBN:
(纸本)9781467309899
2-step maximum likelihood block signal detection employing QR decomposition and m-algorithm (QRm-mLBD) can significantly improve the bit error rate (BER) performance of single-carrier (SC) transmission while reducing the computational complexity compared to maximum likelihood detection (mLD). In 2-step QRm-mLBD, unreliable symbol candidates are removed by performing minimummean square error based frequency-domain equalization (mmSE-FDE) prior to QRm-mLBD. However, a large number m of surviving paths is still required in the m-algorithm to achieve a BER performance close to the matched filter (mF) bound. In this paper, to remedy this problem, we introduce a detection ordering to 2-step QRm-mLBD. We will show by computer simulation that the use of detection ordering can achieve the same BER performance as 2-step QRm-mLBD while reducing the computational complexity.
For high-speed packet access, hybrid automatic repeat request (HARQ) and multi-input multi-output (mImO) multiplexing are indispensable techniques. Single-carrier (SC) mImO block transmission using frequency-domain si...
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ISBN:
(纸本)9781467309899
For high-speed packet access, hybrid automatic repeat request (HARQ) and multi-input multi-output (mImO) multiplexing are indispensable techniques. Single-carrier (SC) mImO block transmission using frequency-domain signal detection such as the frequency-domain linear detection based on the minimummean square error criterion (mmSED) can improve the HARQ throughput performance over the frequency-selective fading channel. However, the performance improvement is limited due to not only an inter-antenna interference (IAI) but also an intersymbol interference (ISI) resulting from a severe frequencyselective fading. In this paper, we propose to jointly use a training sequence (TS) aided SC block transmission and a near maximum likelihood (mL) block detection using QR decomposition and malgorithm (QRm-mLBD) for SC-mImO HARQ. It is shown, by computer simulation, that SC-mImO using TS aided QRmmLBD significantly improves the HARQ throughput performance compared to an often used cyclic prefix (CP) inserted SCmImO while significantly reducing the computational complexity. It is also shown that proposed TS aided QRm-mLBD achieves a significantly higher throughput than the mmSED particularly when higher level modulation is used.
For iterative detection and decoding (IDD) in multiple-input multiple-output (mImO) systems, the mImO detector needs to provide soft-decisions. Since the complexity of the maximum a posteriori probability (mAP) detect...
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For iterative detection and decoding (IDD) in multiple-input multiple-output (mImO) systems, the mImO detector needs to provide soft-decisions. Since the complexity of the maximum a posteriori probability (mAP) detector grows exponentially with the number of transmit antennas, various suboptimal detectors are proposed to exploit the tradeoff between complexity and performance. Among them, the minimummean square error (mmSE)-soft cancellation (SC) detector has an excellent tradeoff. In this paper, by noting that the mmSE-SC detector is an approximate mAP detector, another approximate mAP detector that uses successive processing is proposed. The proposed successive detector can provide a better performance than the mmSE-SC detector, while its complexity is comparable with that of the mmSE-SC detector. An interesting feature of the proposed successive detector is that the tradeoff between complexity and performance can be exploited by a single parameter, which could be an important control parameter in practical implementations.
Soft-decisions from a multiple input multiple output (mImO) detector are desirable if iterative detection and decoding (IDD) is employed at receivers in mImO systems. The minimummean square error (mmSE)-soft cancella...
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ISBN:
(纸本)9781424492688
Soft-decisions from a multiple input multiple output (mImO) detector are desirable if iterative detection and decoding (IDD) is employed at receivers in mImO systems. The minimummean square error (mmSE)-soft cancellation (SC) detector has an excellent trade-off between performance and complexity. By noting that the mmSE-SC detector is an approximate maximum a posteriori probability (mAP) detector, another approximate mAP detector that uses sequential processing is proposed in this paper. The proposed sequential detector can provide a better performance than the mmSE-SC detector, while its complexity is comparable with that of the mmSE-SC detector. An interesting feature of the proposed sequential detector is that the trade-off between complexity and performance can be exploited by a single parameter, which could be an important control parameter in practical implementations.
The use of multiple antennas at both transmitter and receiver can increase wireless communication system capacity enormously. The optimal detection algorithm for mImO system is maximum likelihood detection (mLD) algor...
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ISBN:
(纸本)9783642181337
The use of multiple antennas at both transmitter and receiver can increase wireless communication system capacity enormously. The optimal detection algorithm for mImO system is maximum likelihood detection (mLD) algorithm, which provides the best bit error rate (BER) performance for mImO system. However, the computational complexity of mLD algorithm grows exponentially with the number of transmit antennas and the order of modulation. An improved mImO detection algorithm which combined m-algorithm with stack algorithm was presented in this paper. The proposed algorithm was a multistage detection which was consisted with three parts: mLD, m-algorithm and stack algorithm. In mImO communication system with in transmit antennas, after performing QR decomposition of the channel matrix, the mLD with length L was done firstly. The partial accumulated metrics were calculated and sorted, which produced an ordered set. Then selecting the first m partial symbol vectors to form a new ordered set. Based on the new ordered set, stack algorithm was performed to search for the symbols with the minimum accumulated metrics. The proposed algorithm combining malgorithm and stack algorithm reduced numbers of ordering with the original stack algorithm, the probability of look back and improving the detection performance.
A new 2-step maximum likelihood block signal detection employing QR decomposition and m-algorithm (QRm-mLBD) is proposed to further reduce the computational complexity while keeping a good bit error rate (BER) perform...
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ISBN:
(纸本)9781424483273
A new 2-step maximum likelihood block signal detection employing QR decomposition and m-algorithm (QRm-mLBD) is proposed to further reduce the computational complexity while keeping a good bit error rate (BER) performance for the single-carrier (SC) transmission in a frequency-selective fading channel. Prior to QRm-mLBD, a computationally efficient minimummean square error based frequency-domain equalization (mmSE-FDE) is performed to discard the symbol candidates in the tree based on the soft decision results of mmSE-FDE. We evaluate, by computer simulation, the BER performance achievable by the proposed improved 2-step QRm-mLBD and show that the proposed scheme can reduce the computational complexity compared to the previously proposed conventional 2-step QRm-mLBD while keeping the same BER performance.
QR decomposition combined with m-algorithm (QRD-m) has received great attention recently due to its low-complexity and near-optimum signal detection performance for multiple-input and multiple-output (mImO) systems. I...
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ISBN:
(纸本)9781424464043
QR decomposition combined with m-algorithm (QRD-m) has received great attention recently due to its low-complexity and near-optimum signal detection performance for multiple-input and multiple-output (mImO) systems. In this paper, we propose a rotation-based transformation method and apply it to the QRD-m detector for mImO systems with the commonly used square quadrature amplitude modulation (S-QAm) or amplitude and phase-shift keying (APSK). The QRD-m detector using proposed rotation-based transformation method achieves 50% computation reduction for 4-QAm based mImO systems compared with the original QRD-malgorithm (25% for those with 16-QAm) without sacrificing any performance. The proposed rotated QRD-mmethod achieves performance close to that of the maximum-likelihood (mL) detector for 4-QAmmodulated mImO systems with computational complexity lower than the linear minimummean square error (LmmSE) based detector. The underlying principle of the proposed rotation-based transformation method can be extended to S-QAm (or APSK) modulated mImO systems employing sphere decoding (SD), list sphere decoding (LSD), list sequential sphere decoder (LISS) (or other quasi-maximum-likelihood detectors), and the full mL based methods in a straightforward manner.
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