A link adaptation scheme optimized for wireless JPEG 2000 transmission over realistic MIMO systems

Abot, Julien; Olivier, Christian; Perrine, Clency; Pousset, Yannis

doi:10.1016/j.image.2012.08.003

Cited by 14 publications

(30 citation statements)

References 32 publications

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“…In [21,40], streaming performance is simulated over realistic wireless channels, such as multiple-input multiple-output or Rayleigh fading ones. In [17], the authors conjugate JPWL with a dynamic bandwidth estimation scheme in order to provide the best layering, scaling, and protection of video streams.…”

Section: Review Of Recent Workmentioning

confidence: 99%

Adaptive error protection coding for wireless transmission of motion JPEG 2000 video

Baruffa

Frescura

2016

J Image Video Proc.

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The delivery of video over wireless, error-prone transmission channels requires careful allocation of channel and source code rates, given the available bandwidth. In this paper, we present a theoretical framework to find an optimal joint channel and source code rate allocation, by considering an intra-coded video compression standard such as Motion JPEG 2000 and an error-prone wireless transmission channel. Lagrangian optimization is used to find the optimal code rate allocation, from a PSNR perspective, starting from commonly available source coding outputs, such as intermediate rate-distortion traces. The algorithm is simple and adaptive both on the available bandwidth and on the transmission channel conditions, and it has a low computational complexity. Simulation results, using Reed-Solomon (R-S) coding, show that the achieved performance, in terms of PSNR and MSSIM, is comparable with that of other methods reported in literature. In addition, a simplified and sub-optimal expression for determining the channel code assignment is also provided.

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Section: Review Of Recent Workmentioning

confidence: 99%

Adaptive error protection coding for wireless transmission of motion JPEG 2000 video

Baruffa

Frescura

2016

J Image Video Proc.

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“…In fact, these precoders do not take into account the importance of the quality layer hierarchy and perform optimization on all sub-channels without drawing a correlation between the performance of each one and the quality of reconstructed image. The UPA strategy considered in this paper is achieved using a CBP precoder (Content-Based Precoding) [11]. The CBP precoder is designed to transmit hierarchical quality layers on SISO sub-channels which are also hierarchical.…”

Section: Soft-input Arithmetic Decodingmentioning

confidence: 99%

“…In fact, the transmission of hierarchical bitstream can be exploited in MIMO transmission context, using a Closed-Loop (CL) scheme. This idea has been a focus of active research over the past few years [10], [11], [12], [13]. Recently, Abot et al [11] proposed a JSC solution optimized for wireless image transmission over a MIMO channel.…”

Section: Introductionmentioning

confidence: 99%

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Soft-input arithmetic decoding for optimized scalable image transmission over a realistic MIMO channel

Mhamdi¹,

Zribi²,

Perrine³

et al. 2014

2014 IEEE International Conference on Communication Systems

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International audienceIn this paper, we investigate a new communication strategy for embedded image transmission over a realistic Multiple-Input Multiple-Output (MIMO) wireless channel. The objective of our approach is to guarantee Quality of Service (QoS) required by the user for all possible channel states. In this scope, two major improvements are considered. The first is based on Unequal Power Allocation (UPA) and aims at optimizing the transmit power over the different antennas in order to maximize the image quality at the reception. The second contribution is based on Joint Source-Channel (JSC) soft-input arithmetic decoding and helps to decrease the error rates at the reception without including extra redundancy. We considered Robust SPIHT (R-SPIHT) source encoder to generate an embedded bit-stream. Simulation results illustrate good image quality improvements at the receiver side, with significant Peak Signal to Noise Ratio (PSNR) gains, especially for a realistic noisy channel provided by a 3D ray-tracing software

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“…UEP can be implemented on several levels of the communication systems: on source coding level where many source layers with different importance are produced, on channel coding level using different coding rates for each priority layer, on modulation level with different modulation modes for the priority layers, and on transmission level using MIMO antennas, where better spatial channels are used for the important data. Different levels of the system can also be combined together for better UEP performance [4], [5], [6].…”

Section: Introductionmentioning

confidence: 99%

From source coding to MIMO - a multi-level unequal error protection

Barmada

Rehman

2016

2016 IEEE Region 10 Conference (TENCON)

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Abstract-In this paper, unequal error protection (UEP) on different levels of the transmission system is proposed. Starting from the source coding level, two priority layers are produced, high priority (HP) and low priority (LP). At channel coding, each priority layer is turbo encoded with a coding rate that reflects its importance. For modulation, a more immune modulation mode is used to modulate the HP bit stream. Finally at the transmission level, a 3 × 3 MIMO is used, where more transmit antennas and time slots are offered to HP data. This arrangement of inequality over several levels increases the flexibility of the UEP system and leads to a better performance. Results show that the proposed system outperforms other semi-unequal and equal error protection systems over a wide range of channel signal-to-noise ratio (SNR), especially at low SNR values.

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A link adaptation scheme optimized for wireless JPEG 2000 transmission over realistic MIMO systems

Cited by 14 publications

References 32 publications

Adaptive error protection coding for wireless transmission of motion JPEG 2000 video

Adaptive error protection coding for wireless transmission of motion JPEG 2000 video

Soft-input arithmetic decoding for optimized scalable image transmission over a realistic MIMO channel

From source coding to MIMO - a multi-level unequal error protection

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