Y.-W. Peter Hong, Wan-Jen Huang, C.-C. Jay Kuo's Cooperative Communications and Networking: Technologies and PDF

By Y.-W. Peter Hong, Wan-Jen Huang, C.-C. Jay Kuo

ISBN-10: 1441971939

ISBN-13: 9781441971937

Cooperative and relay communications have lately turn into the main commonly explored subject matters in communications, wherein clients cooperate in transmitting their messages to the vacation spot, rather than traditional networks which function independently and compete between one another for channel assets. because the box has advanced, cooperative communications became a layout idea instead of a particular transmission know-how. this idea has revolutionized the layout of instant networks, permitting elevated insurance, throughput, and transmission reliability whilst traditional transmission recommendations steadily succeed in their limits. Cooperative and relay applied sciences have additionally made their method towards subsequent iteration instant criteria, akin to IEEE802.16 (WiMAX) or LTE, and feature been included into many glossy instant purposes, corresponding to cognitive radio and mystery communications.

Cooperative Communications and Networking: applied sciences and process Design presents a scientific advent to the basic strategies of cooperative communications and relays expertise to let engineers, researchers or graduate scholars to behavior complex learn and improvement during this area.

The contents of the booklet may be summarized as follows:

  • Introduces the reader to numerous cooperation and relay concepts besides a survey of its position in subsequent new release instant standards
  • Reviews easy instant conversation and MIMO innovations for readers new to this field
  • Presents basic cooperative communique and relay innovations for a uncomplicated cooperative entity that involves in basic terms clients and a standard destination
  • Fundamental limits of cooperative and relay channels are defined from the information-theoretic standpoint
  • Describes how cooperative and relay know-how might be built-in with different complicated instant know-how, similar to OFDM and MIMO
  • Introduces a number of cross-layer and networking concerns which may come up in cooperative networks, together with routing, QoS, and safety considerations

Cooperative Communications and Networking: applied sciences and approach Design offers researchers, graduate scholars, and sensible engineers with adequate wisdom of either the historical past of cooperative communications and networking, and power examine instructions.

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Extra info for Cooperative Communications and Networking: Technologies and System Design

Sample text

12 Illustration of the precoding at the transmitter and linear combining at the receiver in MIMO channels. ¹1 x1 z1 ¹2 x2 z2 .. .. .. ¹M xM zM Fig. 13 Illustration of equivalent parallel channels. E s 2 =E Vx 2 =E x 2 ≤ 1. Please note that we have dropped the symbol index n here simply for the ease of notation. At the receiver end, we exploit the SVD of H to separate the transmitted symbols. 73) where w = UH w is an equivalent noise vector with the covariance matrix 2 E[wwH ] = σw I. Since the matrix Σ and the covariance matrix of w are both diagonal, we have produced equivalently M parallel channels with uncorrelated noise as shown in Fig.

Depending on the specific transmit diversity scheme, the data is first preprocessed to form a sequence of transmit symbol vectors {s[n]}, where s[n] = [s1 [n], s2 [n], . . , sNt [n]]T is the vector of symbols to be transmitted over the Nt antennas in the n-th symbol period. The transmitted symbols are assumed to satisfy the sum power constraint Nt E[|sk [n]|]2 ≤ 1. 45) k=1 The signal obtained at the receiver during the n-th symbol period is given by Nt √ y[n] = P hk sk [n] + w[n], k=1 where P is the total transmit power, hk ∼ CN (0, σh2 ) is the channel coefficient between the k-th transmit antenna and the receiver, and w[n] is the AWGN 2 with zero mean and variance σw .

D. complex circularly symmetric Gaussian random variables with zero mean and variance σh2 , for i = 1, 2, · · · , Nt , and j = 1, 2, · · · , Nr . In the following, we will show an Nt × Nr MIMO channel is able to achieve diversity order of Nt Nr when CSI is available at both the transmitter and the receiver. Given the CSI, the transmitter is able to apply the aforementioned SVD technique to decompose the MIMO channel as M = rank(H) orthogonal eigen-channels. , xk = x/ M , where E[|x|2 ] = 1. The signals received over all eigen-channels are combined with the MRC at the receiver, which results in the SNR at the output as M γMIMO = P |μk |2 = 2 M σw m=1 Nt Nr i=1 j=1 P |hi,j |2 , 2 M σw P σ2 which is chi-squared distributed with mean γ = σ2h and 2Nt Nr degrees of w freedom.

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Cooperative Communications and Networking: Technologies and System Design by Y.-W. Peter Hong, Wan-Jen Huang, C.-C. Jay Kuo


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