Prediction of performance of the DVB-SH system relying on mutual information

DVB-SH (Digital Video Broadcasting-Satellite Handled) is a broadcasting standard dedicated to hybrid broadcasting systems combining a satellite and a terrestrial part. On the satellite part, dedicated interleaving and time slicing mechanisms are proposed to mitigate the effects of Land Mobile Satellite (LMS) channel, based on a convolutional interleaver. Depending on the parameters of this interleaver, this mechanism enables to split in time a codeword on duration from 100 ms to about 30s. This mechanism signi?cantly improves the error recovery performance of the code but in literature, exact evaluation at system level of this improvement is missing. The objective of this paper is to propose a prediction method compatible with fast simulations, to quantitatively evaluate the system performance in terms of Packet Error Rate (PER). The main dif?culty is to evaluate the decoding probability of a codeword submitted to several levels of attenuation. The method we propose consists in using as metric the Mutual Information (MI) between coded bit at the emitter side and the received symbol. It is shown that, by averaging the MI over the codeword and by using the decoding performance function g such that PER=g(MI)determined on the Gaussian channel, we can signi?cantly improve the precision of the prediction compared to the two other methods based on SNR and Bit Error Rate (BER). We evaluated these methods on three arti?cial channels where each codeword is transmitted with three or four different levels of attenuations. The prediction error of the SNR-based (resp. the input BER-based) method varies from 0.5 to 1.7 dB (resp. from 0.7 to 1.2 dB) instead of the MI-based method achieves a precision in the order of 0.1 dB in the three cases. We then evaluate this method on real LMS channels with various DVB-SH interleavers and show that the instantaneous PER can also be predicted with high accuracy

Low Complexity V-BLAST MIMO-OFDM Detector by Successive Iterations Reduction

V-BLAST detection method suffers large computational complexity due to its successive detection of symbols. In this paper, we propose a modified V-BLAST algorithm to decrease the computational complexity by reducing the number of detection iterations required in MIMO communication systems. We begin by showing the existence of a maximum number of iterations, beyond which, no significant improvement is obtained. We establish a criterion for the number of maximum effective iterations. We propose a modified algorithm that uses the measured SNR to dynamically set the number of iterations to achieve an acceptable bit-error rate. Then, we replace the feedback algorithm with an approximate linear function to reduce the complexity. Simulations show that significant reduction in computational complexity is achieved compared to the ordinary V-BLAST, while maintaining a good BER performance.Comment: 6 pages, 7 figures, 2 tables. The final publication is available at www.aece.r

Massive MIMO for Internet of Things (IoT) Connectivity

Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design.Comment: Submitted for publicatio

The edge cloud: A holistic view of communication, computation and caching

The evolution of communication networks shows a clear shift of focus from just improving the communications aspects to enabling new important services, from Industry 4.0 to automated driving, virtual/augmented reality, Internet of Things (IoT), and so on. This trend is evident in the roadmap planned for the deployment of the fifth generation (5G) communication networks. This ambitious goal requires a paradigm shift towards a vision that looks at communication, computation and caching (3C) resources as three components of a single holistic system. The further step is to bring these 3C resources closer to the mobile user, at the edge of the network, to enable very low latency and high reliability services. The scope of this chapter is to show that signal processing techniques can play a key role in this new vision. In particular, we motivate the joint optimization of 3C resources. Then we show how graph-based representations can play a key role in building effective learning methods and devising innovative resource allocation techniques.Comment: to appear in the book "Cooperative and Graph Signal Pocessing: Principles and Applications", P. Djuric and C. Richard Eds., Academic Press, Elsevier, 201

Multi-band Oversampled Noise Shaping Analog to Digital Conversion

Oversampled noise shaping analog to digital (A/D) converters, which are commonly known as delta-sigma (ΔΣ) converters, have the ability to convert relatively low bandwidth signals with very high resolution. Such converters achieve their high resolution by oversampling, as well as processing the signal and quantization noise with different transfer functions. The signal transfer function (STF) is typically a delay over the signal band while the noise transfer function (NTF) is designed to attenuate quantization noise in the signal band. A side effect of the NTF is an amplification of the noise outside the signal band. Thus, a digital filter subsequently attenuates the out-of-band quantization noise. The focus of this thesis is the investigation of ΔΣ architectures that increase the bandwidth where high resolution conversion can be achieved. It uses parallel architectures exploiting frequency or time slicing to meet this objective. Frequency slicing involves quantizing different portions of the signal frequency spectrum using several quantizers in parallel and then combining the results of the quantizers to form an overall result. Time slicing involves quantizing various groups of time domain signal samples with different quantizers in parallel and then combining the results of the quantizers to form an overall output. Several interesting observations can be made from this general perspective of frequency and time slicing. Although the representation of a signal are completely equivalent in time or frequency, the thesis shows that this is not the case for known frequency and time sliced A/D architectures. The performance of such systems under ideal conditions are compared for PCM as well as for ΔΣ A/D converters. A multi-band frequency sliced architecture for delta-sigma conversion is proposed and its performance is included in the above comparison. The architecture uses modulators which realize different NTFs for different portions of the signal band. Each band is converted in parallel. A bank of FIR filters attenuates the out of-band noise for each band and achieves perfect reconstruction of the signal component. A design procedure is provided for the design of the filter bank with reduced computational complexity. The use of complex NTFs in the multi-band ΔΣ architecture is also proposed. The peformance of real and complex NTFs is compared. Performance evaluations are made for ideal systems as well as systems suffering from circuit implementation imperfections such as finite opamp gain and mismatched capacitor ratios

Connectivity of the Superficial Muscles of the Human Perineum: A Diffusion Tensor Imaging-Based Global Tractography Study.

Despite the importance of pelvic floor muscles, significant controversy still exists about the true structural details of these muscles. We provide an objective analysis of the architecture and orientation of the superficial muscles of the perineum using a novel approach. Magnetic Resonance Diffusion Tensor Images (MR-DTI) were acquired in 10 healthy asymptomatic nulliparous women, and 4 healthy males. Global tractography was then used to generate the architecture of the muscles. Micro-CT imaging of a male cadaver was performed for validation of the fiber tracking results. Results show that muscles fibers of the external anal sphincter, from the right and left side, cross midline in the region of the perineal body to continue as transverse perinea and bulbospongiosus muscles of the opposite side. The morphology of the external anal sphincter resembles that of the number '8' or a "purse string". The crossing of muscle fascicles in the perineal body was supported by micro-CT imaging in the male subject. The superficial muscles of the perineum, and external anal sphincter are frequently damaged during child birth related injuries to the pelvic floor; we propose the use of MR-DTI based global tractography as a non-invasive imaging technique to assess damage to these muscles

Reduction of HARQ Latency for URLLC 5G Services Based on Network Slicing and Massive MIMO Hybrid Beamforming

Ultra-Reliable and Low-Latency Communications (URLLC)  is one of the three generic 5G services and probably the most challenging one, with strict quality of service requirements of 99.999% or more reliability and <1 milliseconds (ms) radio latency. To achieve latency targets, contributors to latency need to be addressed. Hybrid automatic repeat request (HARQ) retransmissions are major contributor to latency and need to be limited. The objective of this paper is to study the benefit of using Massive MIMO (M-MIMIO) along with radio network slicing to reduce number of HARQ retransmissions. A practical type of M-MIMO beamforming named hybrid beamforming is used. The performance of the proposed system is evaluated with slicing, without slicing and by alternating number of data streams per user. This work highlights the importance of technology enablers, such as M-MIMO and network slicing, in addressing quality-of-service (QoS) latency requirements for URLLC applications