Iterative Detection Technique Research Articles

Combined Deep Learning and SOR Detection Technique for High Reliability in Massive MIMO Systems

In this paper, a novel iterative detection technique that combines deep learning (DL) and the approximated algorithm of successive over relaxation (SOR) is proposed to achieve high reliability and reduce the computational complexity. Recently, as the demanded data rates increase, the massive multiple-input and multiple-output (MIMO) system has drawn attention in wireless communication. In massive MIMO, the implementation of traditional detectors for high reliability has become impractical, and the reduction for the complexity of detectors has emerged as a practical implementation challenge. The existing DL-based detection technique of orthogonal approximate message passing network (OAMPNet) can provide high detection performance. However, the computational complexity is too high for the implementation in massive MIMO systems. The proposed detection technique uses SOR algorithm to reduce the computational complexity, and the relaxation parameter of SOR is adaptively determined by a learning algorithm. A non-linear estimator using the DL algorithm is combined with the SOR algorithm to achieve high reliability, and regardless of the size of the MIMO system, only the size of the DL architecture determines the complexity of the non-linear estimator. Simulation results show that the proposed detector outperforms the conventional linear detector based on minimum mean square error (MMSE) and achieves high reliability with lower complexity than OAMPNet in various channel environments with spatial correlation.

Spectrally Efficient Direct-Detected OFDM Transmission Incorporating a Tunable Frequency Gap and an Iterative Detection Techniques

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> We analytically and experimentally demonstrate a linearly field-modulated, direct-detected virtual single-sideband orthogonal frequency-division multiplexing (VSSB-OFDM) system that employs a tunable frequency gap and an iterative detection technique. The VSSB-OFDM that uses no frequency gap, which is referred to as the gapless VSSB-OFDM, is proposed as a spectrally efficient format. Compared with the intensity-modulated SSB-OFDM, the gapless VSSB-OFDM saves half the electrical bandwidth (BW), and exhibits better receiving sensitivity and more robust tolerance against fiber chromatic dispersion (CD). Furthermore, by incorporating a tunable frequency gap between the optical carrier and the OFDM data sideband, the calculating burden of the iterative detection is greatly alleviated and the system performance can be flexibly improved within moderate iterations. The width of the optimum frequency gap is found to be <formula formulatype="inline"><tex Notation="TeX">${\sim} {\hbox {0.35}}$</tex></formula> sideband BW, which is reached by trading the levels of signal–signal beat interference and the residual image beat interference. Such a gapped VSSB-OFDM system requires fewer iterations to extract the desired data from the interfered signal and exhibits greater robustness against the carrier-to-signal-power ratio (CSPR) variation, compared with the gapless VSSB-OFDM. In this paper, the analytical model of the proposed gapped VSSB-OFDM system will be addressed. In addition, we also successfully conduct a gapped VSSB-OFDM signal transmission over 1600 km of uncompensated standard single-mode fiber (SSMF) with only <formula formulatype="inline"> <tex Notation="TeX">${\sim} {\hbox {3}}$</tex></formula> dB optical SNR (OSNR) penalty, and obtain a significant OSNR sensitivity improvement of <formula formulatype="inline"><tex Notation="TeX">${\sim} {\hbox {8}}$</tex></formula> dB, compared with the gapless VSSB-OFDM, after such a 1600-km fiber link. </para>

ADAPTIVE TRANSMIT ANTENNA SELECTION AND POWER ALLOCATION SCHEME FOR TURBO-BLAST SYSTEM WITH IMPERFECT CHANNEL STATE INFORMATION

In this paper, a new technique that combines adaptive transmit antenna selection, transmit power allocation and iterative detection is introduced for the modifled Turbo-BLAST system. At the transmitter, in order to minimize the BER performance of the overall system, an adaptive transmit antenna selection scheme is proposed to select the appropriate antenna subset for the actual transmission, and the proper power is allocated for the selected antennas subject to the total transmit power constraint. At the receiver the modifled MMSE detector taking the imperfect CSI into account is used to remove the co-antenna interference. Finally the turbo principle is employed for iterative detection to further lower the BER results. Simulation results show that the introduced adaptive transmit antenna selection and power allocation algorithm can signiflcantly improve the BER performance, and the iterative detection technique can further enhance the performance.

Iterative Equalization and Decoding for SFH Spread-Spectrum Communications using Reed–Solomon Codes

A low-complexity, packet-level iterative detection technique is considered for slow-frequency-hop (SFH) spread-spectrum communications in intersymbol-interference (ISI) channels. Maximum-likelihood sequence estimation (MLSE) equalization with state pinning and bounded-distance errors-and-erasures decoding of Reed–Solomon code words are employed within each iteration of equalization and decoding. The design of a bit interleaver is examined for use with the iterative detection technique. The effect of state pinning on the equalizer performance is characterized, and the probability of packet error and the detection complexity of the SFH system are evaluated for a range of static and fading ISI channels. The use of an early-termination criterion is also considered as a way to achieve a tradeoff between performance and detection complexity with the iterative detection technique.