Multimedia over Cognitive Radio Networks: Algorithms, Protocols, and Experiments (Hardcover)

Fei Hu, Sunil Kumar

  • 出版商: CRC
  • 出版日期: 2014-12-03
  • 售價: $3,465
  • 貴賓價: 9.5$3,292
  • 語言: 英文
  • 頁數: 492
  • 裝訂: Hardcover
  • ISBN: 1482214857
  • ISBN-13: 9781482214857
  • 相關分類: Algorithms-data-structuresRadio-networks
  • 立即出貨 (庫存 < 3)

商品描述

With nearly 7 billion mobile phone subscriptions worldwide, mobility and computing have become pervasive in our society and business. Moreover, new mobile multimedia communication services are challenging telecommunication operators. To support the significant increase in multimedia traffic—especially video—over wireless networks, new technological infrastructure must be created. Cognitive Radio Networks (CRNs) are widely regarded as one of the most promising technologies for future wireless communications. This book explains how to efficiently deliver video, audio, and other data over CRNs.

Covering advanced algorithms, protocols, and hardware-/software-based experiments, this book describes how to encode video in a prioritized way to send to dynamic radio links. It discusses different FEC codes for video reliability and explains how different machine learning algorithms can be used for video quality control. It also explains how to use readily available software tools to build a CRN simulation model.

This book explains both theoretical and experimental designs. It describes how universal software radio peripheral (USRP) boards can be used for real-time, high-resolution video transmission. It also discusses how a USRP board can sense the spectrum dynamics and how it can be controlled by GNU Radio software. A separate chapter discusses how the network simulator ns-2 can be used to build a simulated CRN platform.

商品描述(中文翻譯)

全球手機訂閱數量接近70億,移動和計算已經在我們的社會和商業中無所不在。此外,新的移動多媒體通信服務正在挑戰電信運營商。為了支持無線網絡上多媒體流量(尤其是視頻)的顯著增加,需要建立新的技術基礎設施。認知無線電網絡(CRN)被廣泛認為是未來無線通信中最有前景的技術之一。本書解釋了如何在CRN上高效地傳遞視頻、音頻和其他數據。

本書涵蓋了先進的算法、協議和基於硬件/軟件的實驗,描述了如何以優先方式對視頻進行編碼,以便傳送到動態無線鏈路。它討論了不同的前向錯誤更正(FEC)碼以實現視頻可靠性,並解釋了如何使用不同的機器學習算法進行視頻質量控制。它還解釋了如何使用現成的軟件工具構建CRN模擬模型。

本書既解釋了理論設計,也介紹了實驗設計。它描述了如何使用通用軟件無線電外設(USRP)板進行實時、高分辨率的視頻傳輸。它還討論了USRP板如何感知頻譜動態以及如何通過GNU Radio軟件進行控制。另一章討論了如何使用網絡模擬器ns-2構建模擬的CRN平台。