Iterative channel estimation and equalization for underwater acoustic MIMO SFBC OFDM communication

Zhang, Lingling; Han, Jing; Huang, Jianguo; Zhang, Qunfei

doi:10.1109/coa.2016.7535816

Cited by 5 publications

(5 citation statements)

References 12 publications

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“…And the decoding complexity of the scheme shows a better reduction performance than that of the traditional schemes. Zhang et al [27] propose an iterative channel estimation and equalization algorithm for the space frequency block coding (SFBC) based on the MIMO-OFDM transmission system. Simulation shows that the proposed method achieves great output signal to noise ratio (SNR) improvement and shows visible benefit in the bit error ratio through decoding.…”

Section: Related Workmentioning

confidence: 99%

A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE

et al. 2019

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The MIMO-OFDM system fully exploits the advantages of MIMO and OFDM, effectively resisting the channel multipath fading and inter-symbol interference while increasing the data transmission rate. Studies show that it is the principal technical mean for building underwater acoustic networks (UANs) of high performance. As the core, a signal detection algorithm determines the performance and complexity of the MIMO-OFDM system. However, low computational complexity and high performance cannot be achieved simultaneously, especially for UANs with a narrow bandwidth and limited data rate. This paper presents a novel signal detection algorithm based on generalized MMSE. First, we propose a model for the underwater MIMO-OFDM system. Second, we design a signal coding method based on STBC (space-time block coding). Third, we realize the detection algorithm namely GMMSE (generalized minimum mean square error). Finally, we perform a comparison of the algorithm with ZF (Zero Forcing), MMSE (minimum mean square error), and ML (Maximum Likelihood) in terms of the BER (bit error rate) and the CC (computational complexity). The simulation results show that the BER of GMMSE is the lowest one and the CC close to that of ZF, which achieves a tradeoff between the complexity and performance. This work provides essential theoretical and technical support for implementing UANs of high performance.

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Section: Related Workmentioning

confidence: 99%

A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE

et al. 2019

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“…Because of the complexity of underwater acoustic channel and the mutual interference to adjacent frequency bands, the performance is still unsatisfactory. Both the time division cooperative transmission method applied in [9] and MIMO signal processing applied in [6] show superiority in the bit error ratio performance that the bit error ratio reaches 10 −3 at about 17 dB. The performance of the proposed time-reverse-and-forward underwater acoustic cooperative communication method shows a little more progress, since multipath interference is compressed through time-reverse processing, while residue self-information interference is eliminated by additional cancelation.…”

Section: Bit Error Ratio Performancementioning

confidence: 99%

“…Sparsity of underwater acoustic channel is often large in deep sea and calm sea state, while it may be weaker in coastal waters or rough sea state. To this end, a more complex channel Bit error ratio Reference [10] Reference [9] Reference [8] Reference [6] The proposed method Figure 6: Bit error ratio over sparse channel with respect to different signal to noise ratio. is adopted to validate the performance of the proposed timereverse-and-forward underwater acoustic cooperative communication method.…”

Section: Bit Error Ratio Performancementioning

confidence: 99%

“…Comparison of the transmission rate of the proposed time-reverse-and-forward underwater acoustic cooperative communication method to that of the existing cooperative method is shown in Table 1. In Table 1, it can be seen that when the signal to noise ratio is over 15 dB, the transmission rate of the proposed Bit error ratio Reference [10] Reference [9] Reference [8] Reference [6] The proposed method Figure 7: Bit error ratio over complex channel with respect to different signal to noise ratio.…”

Section: Transmission Rate Analysismentioning

confidence: 99%

“…An underwater communication system based on time domain channel equalization is presented in [5], which migrate the multipath induced intersymbol interference through adaptive equalization of time domain samples. To decrease the complexity for equalization in large latency underwater acoustic channel, frequency domain channel equalization is presented in [6], but both of these are insufficient to avoid the short range issue owing to the serious attenuation. To this end, underwater cooperative communication method is proliferated to extend the communication distance, in which data hops from the source to destination through several relays.…”

Section: Introductionmentioning

confidence: 99%

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Time Reversal Aided Bidirectional OFDM Underwater Cooperative Communication Algorithm with the Same Frequency Transmission

et al. 2017

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In underwater acoustic channel, signal transmission may experience significant latency and attenuation that would degrade the performance of underwater communication. The cooperative communication technique can solve it but the spectrum efficiency is lower than traditional underwater communication. So we proposed a time reversal aided bidirectional OFDM underwater cooperative communication algorithm. The algorithm allows all underwater sensor nodes to share the same uplink and downlink frequency simultaneously to improve the spectrum efficiency. Since the same frequency transmission would produce larger intersymbol interference, we adopted the time reversal method to degrade the multipath interference at first; then we utilized the self-information cancelation module to remove the self-signal of OFDM block because it is known for sensor nodes. In the simulation part, we compare our proposed algorithm with the existing underwater cooperative transmission algorithms in respect of bit error ratio, transmission rate, and computation. The results show that our proposed algorithm has double spectrum efficiency under the same bit error ratio and has the higher transmission rate than the other underwater communication methods.

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Study and Comparision of “MIMO-OFDM” Under Acoustic Communication Systems

Ganesh

Rajaprakash

2022

Lecture Notes in Networks and Systems

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Iterative channel estimation and equalization for underwater acoustic MIMO SFBC OFDM communication

Cited by 5 publications

References 12 publications

A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE

A Novel Signal Detection Algorithm for Underwater MIMO-OFDM Systems Based on Generalized MMSE

Time Reversal Aided Bidirectional OFDM Underwater Cooperative Communication Algorithm with the Same Frequency Transmission

Study and Comparision of “MIMO-OFDM” Under Acoustic Communication Systems

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