Uplink Resource Management for Multiuser OFDM Video Transmission Systems: Analysis and Algorithm Design

Wang, Dawei; Toni, Laura; Cosman, Pamela C.; Milstein, L.B.

doi:10.1109/tcomm.2013.032013.120053

Cited by 33 publications

(16 citation statements)

References 24 publications

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“…The video content type in the simulation results is as follows. The video is a travel documentary of CIF size and of length 50 s at 30 fps [13,15]. Each user has different starting time of the same cyclic video.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…where BW is the signal bandwidth, A s,p = η * P s,p * h s,p 2 /P awgn , C p = ∑ N q=1 P w,q * w s,p h w,q 2 /P awgn and η represents the gap to the theoretical capacity [13,15].…”

Section: Received Sinr and Information (Data) Rate Of Usersmentioning

confidence: 99%

“…According to the video distortion model [15], the video MSE of each group of pictures (GOP) of the NOMA system can be approximated as the following equation [31]:…”

Section: Video Mse Distortion Model and Psnrmentioning

confidence: 99%

“…The rate NOMA is either rate s,p in (9) for strong users or rate w,q in ( 13) for weak users. The a k , b k , and c k are fitted before transmission and depend on the video content [15,16,25].…”

Section: Video Mse Distortion Model and Psnrmentioning

confidence: 99%

“…Tseng et al [13] proposed an improved weak user selection scheme in the physical layer, and a power allocation/user substitution scheme in the application layer. This is a cross-layer approach just as with non-NOMA systems [15,16]. Qureshi et al [14] proposed a concept of successive bandwidth division (SBD).…”

Section: Introductionmentioning

confidence: 99%

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User Selection Approach in Multiantenna Beamforming NOMA Video Communication Systems

Tseng

Kao²

2021

Symmetry

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For symmetric non-orthogonal multiple access (NOMA)/multiple-input multiple-output (MIMO) systems, radio resource allocation is an important research problem. The optimal solution is of high computational complexity. Thus, one existing solution Kim et al. proposed is a suboptimal user selection and optimal power assignment for total data rate maximization. Another existing solution Tseng et al. proposed is different suboptimal user grouping and optimal power assignment for sum video distortion minimization. However, the performance of sub-optimal schemes by Kim et al. and Tseng et al. is still much lower than the optimal user grouping scheme. To approach the optimal scheme and outperform the existing sub-optimal schemes, a deep neural network (DNN) based approach, using the results from the optimal user selection (exhaustive search) as the training data, and a loss function modification specific for NOMA user selection to meet the constraint that a user cannot be in both the strong and weak set, and avoid the post processing online computational complexity, are proposed. The simulation results show that the theoretical peak signal-to-noise ratio (PSNR) of the proposed scheme is higher than the state-of-the-art suboptimal schemes Kim et al. and Tseng et al. by 0.7~2.3 dB and is only 0.4 dB less than the optimal scheme at lower online computational complexity. The online computational complexity (testing stage) of the proposed DNN user selection scheme is 60 times less than the optimal user selection scheme. The proposed DNN-based scheme outperforms the existing suboptimal solution, and slightly underperforms the optimal scheme (exhaustive search) at a much lower computation complexity.

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Section: Simulation Resultsmentioning

confidence: 99%

“…where BW is the signal bandwidth, A s,p = η * P s,p * h s,p 2 /P awgn , C p = ∑ N q=1 P w,q * w s,p h w,q 2 /P awgn and η represents the gap to the theoretical capacity [13,15].…”

Section: Received Sinr and Information (Data) Rate Of Usersmentioning

confidence: 99%

“…According to the video distortion model [15], the video MSE of each group of pictures (GOP) of the NOMA system can be approximated as the following equation [31]:…”

Section: Video Mse Distortion Model and Psnrmentioning

confidence: 99%

Section: Video Mse Distortion Model and Psnrmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

User Selection Approach in Multiantenna Beamforming NOMA Video Communication Systems

Tseng

Kao²

2021

Symmetry

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Cross‐layer 1 and 5 user grouping/power allocation/subcarrier allocations for downlink OFDMA/NOMA video communications

Tseng

Tsai

Suo

2019

Int J Communication

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Wang et al proposed cross-layer resource allocation for orthogonal frequency division multiple access (OFDMA) video transmission systems. Unlike Wang et al, we add non-orthogonal multiple access (NOMA) to the downlink OFDMA video transmission system and propose power allocation for users on each subcarrier (cluster) to minimize sum of video mean square error (MSE) to increase the peak signal-to-noise ratio (PSNR), the video quality. For OFDMA/NOMA video communication systems, we propose cross-layer user clustering to reassign the subcarriers based on sum video distortion minimization and derive the optimal power allocation among NOMA users on the same subcarrier to minimize the sum video distortion. Numerical results show that the proposed scheme outperforms the previous OFDMA cross-layer scheme by Wang et al by 2.2 to 4.5 dB in PSNR and previous OFDMA NOMA physical layer scheme by Ali et al by 2 to 4.4 dB in PSNR, when SNR = 15 dB, and the number of users is 6 to 12.KEYWORDS non-orthogonal multiple access, orthogonal frequency division multiple access, power allocation, user pairing

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Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems

Wang

Cosman

2019

Multimed Tools Appl

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We consider multiuser video communication over uplink orthogonal frequency-division multiple access (OFDMA) systems. A cross-layer algorithm of joint bit allocation, packet scheduling and wireless resource assignment are proposed to minimize the end-to-end expected video distortion. Video rate adaptation is performed under the wireless resource constraints. The target number of encoding bits for each video packet is obtained to minimize the estimated distortion based on the online content-based rate-distortion function. Due to the inaccuracy of the rate control algorithm in H.265/HEVC encoding, the actual number of bits may differ from the target. Accordingly, the actual encoder distortion may deviate from the estimated distortion. Then, we propose an iterative algorithm to re-assign wireless resources based on the actual number of encoded bits to obtain the final resource allocation policy and packet scheduling decision. Numerical simulation results show that our proposed approach significantly outperforms the baseline algorithms in terms of received video quality.

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Uplink Resource Management for Multiuser OFDM Video Transmission Systems: Analysis and Algorithm Design

Cited by 33 publications

References 24 publications

User Selection Approach in Multiantenna Beamforming NOMA Video Communication Systems

User Selection Approach in Multiantenna Beamforming NOMA Video Communication Systems

Cross‐layer 1 and 5 user grouping/power allocation/subcarrier allocations for downlink OFDMA/NOMA video communications

Joint rate adaptation and resource allocation for real-time H.265/HEVC video transmission over uplink OFDMA systems

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