tions. Bootstrap has found many applications in engineering field, including artificial neural networks, biomedical engineering, environmental engineering, image processing, and radar and sonar signal processing. Basic concepts of the bootstrap are summarized in each section as a step-by-step algorithm for ease of implementation. Most of the applications are taken from the signal processing literature. The principles of the bootstrap are introduced in Chapter 2. Both the nonparametric and parametric bootstrap procedures are explained. Babu and Singh (1984) have demonstrated that in general, these two procedures behave similarly for pivotal (Studentized) statistics. The fact that the bootstrap is not the solution for all of the problems has been known to statistics community for a long time; however, this fact is rarely touched on in the manuscripts meant for practitioners. It was first observed by Babu (1984) that the bootstrap does not work in the infinite variance case. Bootstrap Techniques for Signal Processing explains the limitations of bootstrap method with an example. I especially liked the presentation style. The basic results are stated without proofs; however, the application of each result is presented as a simple step-by-step process, easy for nonstatisticians to follow. The bootstrap procedures, such as moving block bootstrap for dependent data, along with applications to autoregressive models and for estimation of power spectral density, are also presented in Chapter 2. Signal detection in the presence of noise is generally formulated as a testing of hypothesis problem. Chapter 3 introduces principles of bootstrap hypothesis testing. The topics are introduced with interesting real life examples. Flow charts, typical in engineering literature, are used to aid explanations of the bootstrap hypothesis testing procedures. The bootstrap leads to second-order correction due to pivoting; this improvement in the results due to pivoting is also explained. In the second part of Chapter 3, signal processing is treated as a regression problem. The performance of the bootstrap for matched filters as well as constant false-alarm rate matched filters is also illustrated. Chapters 2 and 3 focus on estimation problems. Chapter 4 introduces bootstrap methods used in model selection. Due to the inherent structure of the subject matter, this chapter may be difficult for nonstatisticians to follow. Chapter 5 is the most impressive chapter in the book, especially from the standpoint of statisticians. It provides real data bootstrap applications to illustrate the theory covered in the earlier chapters. These include applications to optimal sensor placement for knock detection and land-mine detection. The authors also provide a MATLAB toolbox comprising frequently used routines. Overall, this is a very useful handbook for engineers, especially those working in signal processing.

Probability and Random Processes

Wi-Fi Direct is a new technology defined by the Wi-Fi Alliance aimed at enhancing direct device to device communications in Wi-Fi. Thus, given the wide base of devices with Wi-Fi capabilities, and the fact that it can be entirely implemented in software over traditional Wi-Fi radios, this technology is expected to have a significant impact. In this article we provide a thorough overview of the novel functionalities defined in Wi-Fi Direct, and present an experimental evaluation that portrays the performance to be expected in real scenarios. In particular, our results quantify the delays to be expected in practice when Wi-Fi Direct devices discover each other and establish a connection, and the performance of its novel power saving protocols. To the best of the authors? knowledge this is the first article in the state of the art that provides a wide overview and experimental evaluation of Wi-Fi Direct.

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Device-to-device communications with Wi-Fi Direct: overview and experimentation

Device-to-device communications with WFi direct: overview and experimentation.

Since the inception of IEEE 802.11 wireless local area networks (WLANs) in 1997, wireless networking technologies have tremendously grown in the last few decades. The fundamental IEEE 802.11 physical (PHY) and medium access control (MAC) protocols have continuously been enriched with new technologies to provide the last mile wireless broadband connectivity to end users. Consequently, several new amendments of the basic IEEE 802.11 gradually came up in the forms of IEEE 802.11a, IEEE 802.11b, and IEEE 802.11g. More recently, IEEE 802.11n, IEEE 802.11ac, and IEEE 802.11ad are introduced with enhanced PHY and MAC layers that boost up physical data rates to the order of Gigabit per second. So, these amendments are generally known as high throughput WLANs (HT-WLANs). In HT-WLANs, PHY layer is enhanced with multiple-input multiple-output antenna technologies, channel bonding, short guard intervals, enhanced modulation and coding schemes. The MAC sublayer overhead is reduced by introducing frame aggregation and block acknowledgement technologies. However, several existing studies reveal that, many a time, the aforesaid PHY and MAC enhancements yield negative impact on various upper layer protocols, that is end-to-end transport and application layer protocols. As a consequence, a large number of researchers have focused on improving the coordination among PHY/MAC and upper layer protocols. In this survey, we discuss impact of HT-WLAN PHY and MAC layer enhancements on various transport and application layer protocols. This paper also summarizes several research works that use aforesaid enhancements effectively to boost up data rate of end-to-end protocols. We also point out limitations of the existing researches and list down different open challenges that can be meaningfully explored for the development of the next generation HT-WLAN technologies.

Impact of IEEE 802.11n/ac PHY/MAC High Throughput Enhancements on Transport and Application Protocols—A Survey

The added value of Device-to-Device (D2D) communication amounts to an efficient content discovery mechanism that enables users to steer their requests toward the node most likely to satisfy them. In this paper, we address the implementation of content-centric routing in a D2D architecture for Android devices based on WiFi Direct, a protocol recently standardised by the Wi-Fi Alliance. After discussing the creation of multiple D2D groups, we introduce novel paradigms featuring intra- and inter-group bidirectional communication. We then present the primitives involved in content advertising and requesting among members of the multi-group network. Finally, we evaluate the performance of our architecture in a real testbed involving Android devices in different group configurations. We also compare the results against the ones achievable exploiting Bluetooth technologies.

Sebastií Sallent-Ribes

Papers

Designing energy efficient access points with Wi-Fi Direct

Leveraging 802.11n frame aggregation to enhance QoS and power consumption in Wi-Fi networks