This paper presents an equalization algorithm for continuous phase modulation （CPM） over frequency-selective channels. A specific training sequence is first embedded in each data packet. By recursive least-squares ...This paper presents an equalization algorithm for continuous phase modulation （CPM） over frequency-selective channels. A specific training sequence is first embedded in each data packet. By recursive least-squares （RLS） estimation, the channel information parameters can be acquired, and a fractionally Simulation results show that the proposed algorithm can acquire the spaced equalizer performs joint decoding and equalization. channel information parameters rapidly and accurately, and that the fractionally spaced equalizer can eliminate the intersymbol interference （ISI） effectively, and is not sensitive to timing inaccuracy, so this algorithm can be exploited for demodulation system in burst mode.展开更多
A reduced state Soft Input Soft Output (SISO) a posteriori probability algorithm for Seri-ally Concatenated Continuous Phase Modulation (SCCPM) is proposed in this paper. Based on the Reduced State Sequence Detection ...A reduced state Soft Input Soft Output (SISO) a posteriori probability algorithm for Seri-ally Concatenated Continuous Phase Modulation (SCCPM) is proposed in this paper. Based on the Reduced State Sequence Detection (RSSD),it has more general form compared with other reduced state SISO algorithms. The proposed algorithm can greatly reduce the state number,thus leads to the computation complexity reduction. It also minimizes the degradation in Euclidean distance with decision feedback in the reduced state trellis. Analysis and simulation results show that the perform-ance degradation is little with proper reduction scheme.展开更多
This paper first calculates numerically the Symmetric Information Rate (SIR) of Cotinuous Phase Modulation (CPM) schemes over Additive White Gaussian Noise (AWGN) channel, modeling CPM and channel as a Memory-less Mod...This paper first calculates numerically the Symmetric Information Rate (SIR) of Cotinuous Phase Modulation (CPM) schemes over Additive White Gaussian Noise (AWGN) channel, modeling CPM and channel as a Memory-less Modulator (MM) plus a Markov Finite State Channel (FSMC), then proposes an optimal detector, which is of BCJR based Decision Feedback Detector (DFD) but non-iterative. It can achieve the SIR as the sequence length approaches infinity while the complexity is extremely low. Finally, both theoretic proof and numerical simulation are performed to show the op- timality. Simulation results show that it nearly achieves the theoretic bound and outperforms the Viterbi Detector (VD) with 2dB in low Eb/N0.展开更多
The Q-ary low-density parity-check（LDPC） coded high order partial response continuous phase modulation（PR-CPM） with double iterative loops is investigated. This scheme shows significant improvements in power and b...The Q-ary low-density parity-check（LDPC） coded high order partial response continuous phase modulation（PR-CPM） with double iterative loops is investigated. This scheme shows significant improvements in power and bandwidth efficiency, but at the expense of long iterative decoding delay and computational complexity induced by the improper match between the demodulator and the decoder. To address this issue, the convergence behavior of Q-ary LDPC coded CPM is investigated for the Q=2 and Q〉2 cases, and an optimized design method based on the extrinsic information transfer chart is proposed to improve the systematic iterative efficiency. Simulation results demonstrate that the proposed method can achieve a perfect tradeoff between iterative decoding delay and bit error rate performance to satisfy real-time applications.展开更多
This paper proposes a new two-branch amplification architecture that combines baseband signal decomposition with RF front-end optimization. In the proposed architecture, the filtered modulated signals are separated in...This paper proposes a new two-branch amplification architecture that combines baseband signal decomposition with RF front-end optimization. In the proposed architecture, the filtered modulated signals are separated into two components that are then amplified independently and combined to regenerate an amplified version of the original signal. A branch with an efficient amplifier transmits a low-varying envelope signal that contains the main part of the information. Another branch amplifies the residual portion of the signal. The baseband decomposition and parameters of the RF part are optimized to find the configuration that gives the best power efficiency and linearity. For M-ary quadrature amplitude modulation （M-QAM） signals, this technique is limited in terms of power efficiency. However, for filtered continuous phase modulation （CPM） signals, especially for minimum shift keying （MSK） and Gaussian MSK （GMSK） signals, high power efficiency can be achieved with no significant impact on the overall linearity. The results show that this technique gives better performance than the single-ended ctass-B amplifier.展开更多
The continuous phase modulation(CPM)technique is widely used in range telemetry due to its high spectral efficiency and power efficiency.However,the demodulation performance of the traditional maximum likelihood seque...The continuous phase modulation(CPM)technique is widely used in range telemetry due to its high spectral efficiency and power efficiency.However,the demodulation performance of the traditional maximum likelihood sequence detection(MLSD)algorithm significantly deteriorates in non-ideal synchronization or fading channels.To address this issue,this work proposes a convolutional neural network(CNN)called the cascade parallel crossing network(CPCNet)to enhance the robustness of CPM signals demodulation.The CPCNet model employs a multiple parallel structure and feature fusion to extract richer features from CPM signals.This approach constructs feature maps at different levels,resulting in a more comprehensive training of the model and improved demodulation performance.Simulation results show that under Gaussian channel,the proposed CPCNet achieves the same bit error rate(BER)performance as MLSD method when there is no timing error,but with 1/4 symbol period timing error,the proposed method has 2 dB demodulation gain compared with CNN and convolutional long short-term memory deep neural network(CLDNN).In addition,under Rayleigh channel,the BER of the proposed method is reduced by 5%-87%compared to that of MLSD in the wide signal-to-noise ratio(SNR)region.展开更多
In this paper, serially concatenated continuous phase modulation （SCCPM） system is analyzed and a reduced state soft input soft output （SlSO） a posteriori probability algorithm is proposed. Based on the reduced st...In this paper, serially concatenated continuous phase modulation （SCCPM） system is analyzed and a reduced state soft input soft output （SlSO） a posteriori probability algorithm is proposed. Based on the reduced state sequence detection （RSSD）, it has the more general form compared with other reduced state SISO algorithms. The proposed algorithm can greatly reduce the state number, thus leads to the computation complexity reduction. It also minimizes the degradation in Euclidean distance with decision feedback in the reduced state trellis. Analysis and simulation results show that the performance degradation is little with proper reduction scheme.展开更多
In order to solve the problem of high computational complexity in demodulation for multi-h continuous phase modulation(CPM) signal, a maximum cumulative measure combing with the Laurent decomposition(MCM-LD) scheme is...In order to solve the problem of high computational complexity in demodulation for multi-h continuous phase modulation(CPM) signal, a maximum cumulative measure combing with the Laurent decomposition(MCM-LD) scheme is proposed to reduce the number of the grid states and the required number of matched filters, which degrades the demodulation complexity at the receiver.The advanced range telemetry(ARTM) Tier Ⅱ CPM signal is adopted to evaluate the performance in simulation. The results show that, compared with the traditional maximum likelihood sequence detection(MLSD), MCM-LD can respectively reduce the numbers of grid states and matched filters from 256 to 32 and 128 to 48 with negligible performance loss, which effectively degrades the computational complexity for multi-h CPM signal.展开更多
文摘This paper presents an equalization algorithm for continuous phase modulation （CPM） over frequency-selective channels. A specific training sequence is first embedded in each data packet. By recursive least-squares （RLS） estimation, the channel information parameters can be acquired, and a fractionally Simulation results show that the proposed algorithm can acquire the spaced equalizer performs joint decoding and equalization. channel information parameters rapidly and accurately, and that the fractionally spaced equalizer can eliminate the intersymbol interference （ISI） effectively, and is not sensitive to timing inaccuracy, so this algorithm can be exploited for demodulation system in burst mode.
基金Supported by NSFC & Microsoft Asia (60372048)China TRAPOYT, NSFC key project (60496316)+2 种基金863 Project (2005AA123910)RFDP (20050701007)MOE Key Project (104171).
文摘A reduced state Soft Input Soft Output (SISO) a posteriori probability algorithm for Seri-ally Concatenated Continuous Phase Modulation (SCCPM) is proposed in this paper. Based on the Reduced State Sequence Detection (RSSD),it has more general form compared with other reduced state SISO algorithms. The proposed algorithm can greatly reduce the state number,thus leads to the computation complexity reduction. It also minimizes the degradation in Euclidean distance with decision feedback in the reduced state trellis. Analysis and simulation results show that the perform-ance degradation is little with proper reduction scheme.
基金Supported by the Key Industrial Research of Zhejiang Province (No. 2006C21009).
文摘This paper first calculates numerically the Symmetric Information Rate (SIR) of Cotinuous Phase Modulation (CPM) schemes over Additive White Gaussian Noise (AWGN) channel, modeling CPM and channel as a Memory-less Modulator (MM) plus a Markov Finite State Channel (FSMC), then proposes an optimal detector, which is of BCJR based Decision Feedback Detector (DFD) but non-iterative. It can achieve the SIR as the sequence length approaches infinity while the complexity is extremely low. Finally, both theoretic proof and numerical simulation are performed to show the op- timality. Simulation results show that it nearly achieves the theoretic bound and outperforms the Viterbi Detector (VD) with 2dB in low Eb/N0.
基金supported by the National Natural Science Foundation of China(61403093)the Science Foundation of Heilongjiang Province of China for Returned Scholars(LC2013C22)the Assisted Project by Heilongjiang Province of China Postdoctoral Funds for Scientific Research Initiation(LBH-Q14048)
文摘The Q-ary low-density parity-check（LDPC） coded high order partial response continuous phase modulation（PR-CPM） with double iterative loops is investigated. This scheme shows significant improvements in power and bandwidth efficiency, but at the expense of long iterative decoding delay and computational complexity induced by the improper match between the demodulator and the decoder. To address this issue, the convergence behavior of Q-ary LDPC coded CPM is investigated for the Q=2 and Q〉2 cases, and an optimized design method based on the extrinsic information transfer chart is proposed to improve the systematic iterative efficiency. Simulation results demonstrate that the proposed method can achieve a perfect tradeoff between iterative decoding delay and bit error rate performance to satisfy real-time applications.
文摘This paper proposes a new two-branch amplification architecture that combines baseband signal decomposition with RF front-end optimization. In the proposed architecture, the filtered modulated signals are separated into two components that are then amplified independently and combined to regenerate an amplified version of the original signal. A branch with an efficient amplifier transmits a low-varying envelope signal that contains the main part of the information. Another branch amplifies the residual portion of the signal. The baseband decomposition and parameters of the RF part are optimized to find the configuration that gives the best power efficiency and linearity. For M-ary quadrature amplitude modulation （M-QAM） signals, this technique is limited in terms of power efficiency. However, for filtered continuous phase modulation （CPM） signals, especially for minimum shift keying （MSK） and Gaussian MSK （GMSK） signals, high power efficiency can be achieved with no significant impact on the overall linearity. The results show that this technique gives better performance than the single-ended ctass-B amplifier.
基金Supported by the Beijing Natural Science Foundation (L202003)。
文摘The continuous phase modulation(CPM)technique is widely used in range telemetry due to its high spectral efficiency and power efficiency.However,the demodulation performance of the traditional maximum likelihood sequence detection(MLSD)algorithm significantly deteriorates in non-ideal synchronization or fading channels.To address this issue,this work proposes a convolutional neural network(CNN)called the cascade parallel crossing network(CPCNet)to enhance the robustness of CPM signals demodulation.The CPCNet model employs a multiple parallel structure and feature fusion to extract richer features from CPM signals.This approach constructs feature maps at different levels,resulting in a more comprehensive training of the model and improved demodulation performance.Simulation results show that under Gaussian channel,the proposed CPCNet achieves the same bit error rate(BER)performance as MLSD method when there is no timing error,but with 1/4 symbol period timing error,the proposed method has 2 dB demodulation gain compared with CNN and convolutional long short-term memory deep neural network(CLDNN).In addition,under Rayleigh channel,the BER of the proposed method is reduced by 5%-87%compared to that of MLSD in the wide signal-to-noise ratio(SNR)region.
基金the National Natural Science Foundation of China (Grant Nos. 60496316, 60532060 and 60572146)the Research Fund for the Doctoral Program of Higher Education (Grant No. 20050701007)China Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institutions of MOE, MOE Key Project (Grant No. 107103)
文摘In this paper, serially concatenated continuous phase modulation （SCCPM） system is analyzed and a reduced state soft input soft output （SlSO） a posteriori probability algorithm is proposed. Based on the reduced state sequence detection （RSSD）, it has the more general form compared with other reduced state SISO algorithms. The proposed algorithm can greatly reduce the state number, thus leads to the computation complexity reduction. It also minimizes the degradation in Euclidean distance with decision feedback in the reduced state trellis. Analysis and simulation results show that the performance degradation is little with proper reduction scheme.
文摘In order to solve the problem of high computational complexity in demodulation for multi-h continuous phase modulation(CPM) signal, a maximum cumulative measure combing with the Laurent decomposition(MCM-LD) scheme is proposed to reduce the number of the grid states and the required number of matched filters, which degrades the demodulation complexity at the receiver.The advanced range telemetry(ARTM) Tier Ⅱ CPM signal is adopted to evaluate the performance in simulation. The results show that, compared with the traditional maximum likelihood sequence detection(MLSD), MCM-LD can respectively reduce the numbers of grid states and matched filters from 256 to 32 and 128 to 48 with negligible performance loss, which effectively degrades the computational complexity for multi-h CPM signal.
