Exact symbol error probability of a Cooperative network in a Rayleigh-fading environment
IEEE Transactions on Wireless Communications
Modulation and demodulation for cooperative diversity in wireless systems
IEEE Transactions on Wireless Communications
Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels
IEEE Transactions on Information Theory
The golden code: a 2×2 full-rate space-time code with nonvanishing determinants
IEEE Transactions on Information Theory
On the achievable diversity-multiplexing tradeoff in half-duplex cooperative channels
IEEE Transactions on Information Theory
Optimal Space–Time Codes for the MIMO Amplify-and-Forward Cooperative Channel
IEEE Transactions on Information Theory
Towards the Optimal Amplify-and-Forward Cooperative Diversity Scheme
IEEE Transactions on Information Theory
Cooperative communication in wireless networks
IEEE Communications Magazine
A simple transmit diversity technique for wireless communications
IEEE Journal on Selected Areas in Communications
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In this paper, we present three new detection schemes for the nonorthogonal amplify and forward (NAF) protocol in a cooperative diversity system based on a multiuser detection approach, namely, a channel inversion type detector, a maximal-ratio combining (MRC) type detector, and a biased maximum likelihood (ML) detector. The decision variables in these schemes are linear functionals of the transmitted symbol vector and therefore they are termed as "linear" detectors. A cooperative relay network using the NAF protocol with N - 1 relays is considered where the source transmits symbols in N -1 blocks of two time slots in a Rayleigh fading environment. For the case of a general linear space-time block coding scheme using K symbols, we present the performance of this protocol in terms of the code symbol error probability when the symbols come from an M-ary phase-shift keying constellation. The approach is further extended to the transmission in N -1 blocks of L time slots. Numerical results show that the performance of the MRC type detector is superior to that of the channel inversion type detector, while the biased ML detector has the best performance. However, the MRC type detector has the lowest complexity while the biased ML detector the highest.