Joint-Mapping Orthogonal Frequency Division Multiplexing With Subcarrier Number Modulation

Wen, Miaowen; Li, Jun; Dang, Shuping; Li, Qiang; Mumtaz, Shahid; Arslan, Hüseyin

doi:10.1109/tcomm.2021.3066584

Cited by 42 publications

(15 citation statements)

References 41 publications

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“…However, for future B5G and 6G cellular networks, multi-carrier communication based on OFDM is still a mainstream for boosting system capacity. Specifically, compared with single-carrier relaying, OFDM relaying brings about additional degreesof-freedom for the relay to pair the incoming and outgoing subcarriers according to their signal-to-noise ratios (SNRs), therefore substantially improving the relaying performance [33], [34]. Conventionally, the optimal subcarrier matching for maximizing the sum-SNR over all subcarrier pairs is achieved by the best-to-best (BTB) scheme, i.e., the best subcarrier of the first hop with the highest SNR is paired with the best subcarrier of the second hop, and so on and so forth.…”

Section: Introductionmentioning

confidence: 99%

Reconfigurable Intelligent Surface Assisted OFDM Relaying: Subcarrier Matching with Balanced SNR

Zhang¹,

Wang²,

Zhuang³

et al. 2022

Preprint

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Reconfigurable intelligent surface (RIS) is a promising solution to enhance the performance of wireless communications via reconfiguring the wireless propagation environment. In this paper, we investigate the joint design of RIS passive beamforming and subcarrier matching in RIS-assisted orthogonal frequency division multiplexing (OFDM) dual-hop relaying systems under two cases, depending on the presence of the RIS reflected link from the source to the destination in the first hop. Accordingly, we formulate a mixed-integer nonlinear programming (MINIP) problem to maximize the sum achievable rate over all subcarriers by jointly optimizing the RIS passive beamforming and subcarrier matching. To solve this challenging problem, we first develop a branch-and-bound (BnB)based alternating optimization algorithm to obtain a near-optimal solution by alternatively optimizing the subcarrier matching by the BnB method and the RIS passive beamforming by using semidefinite relaxation techniques. Then, a low-complexity difference-of-convex penalty-based algorithm is proposed to reduce the computation complexity in the BnB method. To further reduce the computational complexity, we utilize the learningto-optimize approach to learn the joint design obtained from optimization techniques, which is more amenable to practical implementations. Lastly, computer simulations are presented to evaluate the performance of the proposed algorithms in the two cases. Simulation results demonstrate that the RIS-assisted OFDM relaying system achieves sustainable achievable rate gain as compared to that without RIS, and that with random passive beamforming, since RIS passive beamforming can be leveraged to recast the subcarrier matching among different subcarriers and balance the signal-to-noise ratio within each subcarrier pair.

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Section: Introductionmentioning

confidence: 99%

Reconfigurable Intelligent Surface Assisted OFDM Relaying: Subcarrier Matching with Balanced SNR

Zhang¹,

Wang²,

Zhuang³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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“…Furthermore, these two approaches are only applicable to the over-determined systems [20]. Recently, a low complexity logarithmic likelihood ratio (LLR) detection algorithm is employed in the joint mapping non-orthogonal frequency division multiplexing with subcarrier number modulation (JM-OFDM-SNM) scheme in [21]. Compared with ML, the LLR detector scheme has no obvious attenuation in performance, while the detection complexity is significantly reduced.…”

Section: Introductionmentioning

confidence: 99%

Sparsity Signal Detection for Indoor GSSK-VLC System

Zuo

Wang

Zhang

2021

IEEE Trans. Veh. Technol.

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In this paper, the signal detection problem in indoor visible light communication (VLC) system aided by generalized space shift keying (GSSK) is modeled as a sparse signal reconstruction problem, which has lower computational complexity by exploiting the sparse reconstruction algorithms in compressed sensing (CS). In order to satisfy the measurement matrix property to perform sparse signal reconstruction, a preprocessing approach of measurement matrix is proposed based on singular value decomposition (SVD), which theoretically guarantees the feasibility of utilizing CS based sparse signal detection method in indoor GSSK-VLC system. Then, by adopting classical orthogonal matching pursuit (OMP) algorithm and compressed sampling matching pursuit (CoSaMP) algorithm, the GSSK signals are efficiently detected in the considered indoor GSSK-VLC system. Furthermore, a more efficient detection algorithm combined with OMP and maximum likelihood (ML) is also presented especially for SSK scenario. Finally, the effectiveness of the proposed sparsity aided detection algorithms in indoor GSSK-VLC system are verified by computer simulations. The results show that the proposed algorithms can achieve better bit error rate (BER) and lower computation complexity than ML based detection method. Specifically, a signal-to-noise ratio (SNR) gain as high as 12 dB is observed in the SSK scenario and about 5 dB in case of a GSSK scenario upon employing our proposed detection methods.

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“…Cooperative relaying is introduced to extend the coverage and improve energy efficiency of OFDM-SNM [23]. Joint mapping technique is applied to OFDM-SNM to allow a constant length of information bits transmitted by OFDM-SNM blocks [24]. Smart detector based on cascaded neural computing is designed to realize low-computational detection of OFDM-SNM blocks [25].…”

Section: Introductionmentioning

confidence: 99%

Information-Theoretic Analysis of OFDM With Subcarrier Number Modulation

Dang

Guo

Shihada

et al. 2021

IEEE Trans. Inform. Theory

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With the prevalence of orthogonal frequencydivision multiplexing (OFDM) in many standards, e.g., IEEE 802.11, IEEE 802.16, DVB-T, and DVB-T2, a number of variant modulation schemes based on OFDM have been proposed, which resort to signal sparsity to further enhance spectral efficiency and mitigate the high peak-to-average ratio (PAPR) problem. Among these variants, OFDM with subcarrier number modulation (OFDM-SNM) has been proven to be efficient for simple communication systems with low constellation modulation orders and limited decoding capability. To rigorously verify the performance advantages of OFDM-SNM, we present the study of OFDM-SNM in this paper from the information-theoretic perspective. In particular, we determine an upper bound on the mutual information of OFDM-SNM in closed form by using the log sum inequality. Also, we analyze the optimal pattern utilization probabilities (PUPs) for OFDM-SNM by channel-dependent coding and propose an easy-to-implement iterative algorithm to approach the optimal PUPs. Moreover, considering the practical achievability, we propose a Huffman coding based achievable PUP vector construction scheme to obtain the achievable PUPs and the corresponding achievable rate. We carry out numerical simulations to verify the effectiveness of this study and illustrate the efficiency of the obtained PUPs in comparison with several benchmarks.

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Joint-Mapping Orthogonal Frequency Division Multiplexing With Subcarrier Number Modulation

Cited by 42 publications

References 41 publications

Reconfigurable Intelligent Surface Assisted OFDM Relaying: Subcarrier Matching with Balanced SNR

Reconfigurable Intelligent Surface Assisted OFDM Relaying: Subcarrier Matching with Balanced SNR

Sparsity Signal Detection for Indoor GSSK-VLC System

Information-Theoretic Analysis of OFDM With Subcarrier Number Modulation

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