Spread Spectrum Signals for Digital Communications

Proakis, J.G.

doi:10.1002/0471219282.eot296

Cited by 464 publications

(842 citation statements)

References 16 publications

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“…In Fig. 7, we further compare 2P-DNF-TWR with the typical receive diversity system using one transmit antenna and receive antenna (1Tx Rx), which is well known to have a diversity order of [23,]. It is clear that the diversity order of the system having 1 relay or 2 relays is 1 as 1Tx1Rx, and the system having 3 relays or 4 relays has a diversity order of 2 as 1Tx2Rx, which validates our proposition (49).…”

Section: Numerical Resultsmentioning

confidence: 99%

“…After expanding (34) by use of the law of total probability, we have (36) on the top of next page, where we use in (a) the fact thatˆ, ( ) is independent of ( ) conditioned on ( ), and in (b) we rely on the fact that the two kinds of conditional decoding error of a typical non-coherent DBPSK decoder are equal and are given by [23,…”

Section: B Source Decoding Errormentioning

confidence: 99%

“…Therefore, more power should be allocated to the sources in order to reduce the relay decoding error. Secondly, the BER of the direct transmission with non-coherent DBPSK modulation scales as −1 [23,], which decreases faster than the dominant error term , at high SNRs. In other words, 2P-DNF-TWR is comparatively not preferred than direct transmission when SNR is increasing, and our simulation results would show this fact later.…”

Section: Power Allocationmentioning

confidence: 99%

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Performance Analysis of Two-Way Relaying with Non-Coherent Differential Modulation

Guan

Liu

2011

IEEE Trans. Wireless Commun.

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Abstract-This work focuses on a two-way denoise-andforward relaying system using non-coherent Differential Binary Phase-Shift Keying (DBPSK) modulation, which has the welldefined relay denoising function when channel state information is unknown. We first design the relay denoising function and source decoders using Maximum Likelihood (ML) principles for the general case with parallel relays. As the ML denoising function is hard to manipulate, we approximate it as a multi-user detector followed by a physical layer network coding encoder and obtain the closed-form relay decoding error. For the singlerelay case, we show that the ML source decoder is actually equivalent to the typical DBPSK decoder for the relay-source channel and thus derive the exact end-to-end Bit Error Rate (BER). To minimize the average BER, we also investigate the power allocation problem by use of asymptotic analysis at high Signal-to-Noise Ratio (SNR). We show that the optimal source power is inversely proportional to the square root of the channel gain of the source-relay channel, and the optimal relay power decreases with SNR. For the multi-relay case, though the exact analysis is intractable, we develop upper bound and lower bound on BER and show that the diversity order is exactly ⌈ 2 ⌉ .Index Terms-Two-way relaying, differential modulation, BER, diversity order, power allocation.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: B Source Decoding Errormentioning

confidence: 99%

Section: Power Allocationmentioning

confidence: 99%

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Performance Analysis of Two-Way Relaying with Non-Coherent Differential Modulation

Guan

Liu

2011

IEEE Trans. Wireless Commun.

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“…The same method is used for BFSK. Since ( ) = (√ ) for BFSK, the probability of bit error rate in the presence of Rayleigh fading channel is (1-√ ) [3]. Those equations show that the BER of BFSK is greater than the BER of BPSK with the same .…”

Section: Modeling a Bfsk And Bpsk With Simulinkmentioning

confidence: 96%

“…The probability of bit error for coherently detected BPSK is defined as: ( ) = (√ ) and the probability of bit error for coherently detected binary orthogonal FSK is: ( ) = (√ ) [3] where is a function of received signal to noise ratio .…”

Section: Time Variance Viewed In the Doppler Shift Domainmentioning

confidence: 99%