A 3-D Polarization Quadrature Amplitude Modulation Method and Constellation Mapping

As a new three-dimensional(3-D)modulation,Polarization Quadrature Amplitude Modulation(PQAM) can be regarded as the combination of Pulse amplitude modulation(PAM) and Quadrature Amplitude Modulation(QAM) Modulation.It can better improve the digital communication efficiency and reduce the Symbol error rate(SER) of the system than one-dimensional or two-dimensional modulation scheme.How to design a feasible constellation is the most concerned problem of PQAM currently.This paper first studies the relationship between the SER theoretical value of PQAM and the distribution of M and N,proposes a new M,N allocation scheme.Secondly,a new and straightforward design method of constructing higher-level 3-D signal constellations,which can be matched with the PQAM,and the constellation can divided into three different structures according to the ary for PQAM.Finally,the simulation results show that:in PQAM system,the modulation scheme and the constellation mapping scheme are proposed in this paper which can effectively reduce the system SER and improve the anti-noise performance of the system.

A novel mapping scheme and modified decoding algorithm for BICM-ID

This paper proposes a novel mapping scheme for bit-interleaved coded modulation with iterative decoding(BICM-ID).The symbol mapping is composed of two QPSK with different radiuses and phases,called cross equalization-8PSK-quasi-semi set partitioning(CE-8PSK-Quasi-SSP).Providing the same average power,the proposed scheme can increase the minimum squared Euclidean distance(MSED)and then improve the receiving performance of BICM-ID compared with conventional symbol mapping schemes.Simultaneously,a modified iteration decoding algorithm is proposed in this paper.In the process of iteration decoding,different proportion of the extrinsic information to the systematic observations results in distinct decoding performance.At high SNR(4~9dB),the observation information plays a more important role than the extrinsic information.Simulation results show that the proportion set at 1.2 is more suitable for the novel mapping in BICM-ID.When the BER is 10^(-4),more than 0.9dB coding gain over Rayleigh channels can be achieved for the improved mapping and decoding scheme.

Four-Dimensional Signal Constellations Based on Binary Frequency-Shift Keying and <i>M</i>-ary Amplitude-Phase-Shift Keying

In this article, we give the construction of new four-dimensional signal constellations in the Euclidean space, which represent a certain combination of binary frequency-shift keying (BFSK) and M-ary amplitude-phase-shift keying (MAPSK). Description of such signals and the formulas for calculating the minimum squared Euclidean distance are presented. We have developed an analytic building method for even and odd values of M. Hence, no computer search and no heuristic methods are required. The new optimized BFSK-MAPSK (M = 5,6,···,16) signal constructions are built for the values of modulation indexes h =0.1,0.15,···,0.5 and their parameters are given. The results of computer simulations are also provided. Based on the obtained results we can conclude, that BFSK-MAPSK systems outperform similar four-dimensional systems both in terms of minimum squared Euclidean distance and simulated symbol error rate.

A NEW LABELING SEARCH ALGORITHM FOR BIT-INTERLEAVED CODED MODULATION WITH ITERATIVE DECODING

Bit-Interleaved Coded Modulation with Iterative Decoding (BICM-ID) is a bandwidth ef- ficient transmission, where the bit error rate is reduced through the iterative information exchange between the inner demapper and the outer decoder. The choice of the symbol mapping is the crucial design parameter. This paper indicates that the Harmonic Mean of the Minimum Squared Euclidean (HMMSE) distance is the best criterion for the mapping design. Based on the design criterion of the HMMSE distance, a new search algorithm to find the optimized labeling maps for BICM-ID system is proposed. Numerical results and performance comparison show that the new labeling search method has a low complexity and outperforms other labeling schemes using other design criterion in BICM-ID system, therefore it is an optimized labeling method.

Radar automatic target recognition based on feature extraction for complex HRRP

Radar high-resolution range profile （HRRP） has received intensive attention from the radar automatic target recognition （RATR） community. Usually, since the initial phase of a complex HRRP is strongly sensitive to target position variation, which is referred to as the initial phase sensitivity in this paper, only the amplitude information in the complex HRRP, called the real HRRP in this paper, is used for RATR, whereas the phase information is discarded. However, the remaining phase information except for initial phases in the complex HRRP also contains valuable target discriminant information. This paper proposes a novel feature extraction method for the complex HRRP. The extracted complex feature vector, referred to as the complex feature vector with difference phases, contains the difference phase information between range cells but no initial phase information in the complex HRRR According to the scattering center model, the physical mechanism of the proposed complex feature vector is similar to that of the real HRRP, except for reserving some phase information independent of the initial phase in the complex HRRP. The recognition algorithms, frame-template establishment methods and preprocessing methods used in the real HRRP-based RATR can also be applied to the proposed complex feature vector-based RATR. Moreover, the components in the complex feature vector with difference phases approximate to follow Gaussian distribution, which make it simple to perform the statistical recognition by such complex feature vector. The recognition experiments based on measured data show that the proposed complex feature vector can obtain better recognition performance than the real HRRP if only the cell interval parameters are properly selected.

Data recovery with sub-Nyquist sampling:fundamental limit and a detection algorithm

While the Nyquist rate serves as a lower bound to sample a general bandlimited signal with no information loss,the sub-Nyquist rate may also be sufficient for sampling and recovering signals under certain circumstances.Previous works on sub-Nyquist sampling achieved dimensionality reduction mainly by transforming the signal in certain ways.However,the underlying structure of the sub-Nyquist sampled signal has not yet been fully exploited.In this paper,we study the fundamental limit and the method for recovering data from the sub-Nyquist sample sequence of a linearly modulated baseband signal.In this context,the signal is not eligible for dimension reduction,which makes the information loss in sub-Nyquist sampling inevitable and turns the recovery into an under-determined linear problem.The performance limits and data recovery algorithms of two different sub-Nyquist sampling schemes are studied.First,the minimum normalized Euclidean distances for the two sampling schemes are calculated which indicate the performance upper bounds of each sampling scheme.Then,with the constraint of a finite alphabet set of the transmitted symbols,a modified time-variant Viterbi algorithm is presented for efficient data recovery from the sub-Nyquist samples.The simulated bit error rates(BERs)with different sub-Nyquist sampling schemes are compared with both their theoretical limits and their Nyquist sampling counterparts,which validates the excellent performance of the proposed data recovery algorithm.