Abstract-In this paper, a novel unified channel model framework is proposed for cooperative multiple-input multiple-output (MIMO) wireless channels. The proposed model framework is generic and adaptable to multiple cooperative MIMO scenarios by simply adjusting key model parameters. Based on the proposed model framework and using a typical cooperative MIMO communication environment as an example, we derive a novel geometry-based stochastic model (GBSM) applicable to multiple wireless propagation scenarios. The proposed GBSM is the first cooperative MIMO channel model that has the ability to investigate the impact of the local scattering density (LSD) on channel characteristics. From the derived GBSM, the corresponding multi-link spatial correlation functions are derived and numerically analyzed in detail.Index Terms-Cooperative MIMO channels, geometry-based stochastic model, spatial correlation, non-isotropic scattering.
The hybrid relay selection (HRS) scheme, which adaptively chooses amplify-and-forward (AF) and decode-and-forward (DF) protocols, is very effective to achieve robust performance in wireless networks. This paper analyzes the frame error rate (FER) of the HRS scheme in general cooperative wireless networks without and with utilizing error control coding at the source node. We first develop an improved signal-to-noise ratio (SNR) threshold-based FER approximation model. Then, we derive an analytical average FER expression as well as an asymptotic expression at high SNR for the HRS scheme and generalize to other relaying schemes. Simulation results are in excellent agreement with the theoretical analysis, which validates the derived FER expressions.
Index TermsHybrid relay selection, frame error rate, SNR threshold-based approximation, cooperative communications.
which is then solved by a GP solver, e.g., gpcvx or MOSEK based on state-of-the-art interior-point method (IPM).An important subtlety should be noted. When all globally optimumx for (11) contains zero entries, the corresponding optimum y for (12) contains entries equal to 01. In such a case, the IPM iteratively outputs y with g 0 (y) asymptotically approaching the optimum objective value for (12), which leads to an overflow in the processor running the GP solver that implements the IPM. It is rarely known a priori if the optimum x for (11) contains zero entries. To avoid overflow, the GP solver by default adds entrywise lower-bound constraints on x, or equivalently on y before solving (12) (see [21, p. 3]). These constraints should be set to ensure that the optimum x for (11) with the extra constraints corresponds to an objective value within a prescribed small tolerance around the original optimum objective for (11).
ACKNOWLEDGMENTThe authors would like to thank Prof. M. Dong and the anonymous reviewers for their precious comments and suggestions which has improved this work.
REFERENCES[1] R. Cendrillon, W. Yu, M. Moonen, J. Verlinden, and T. Bostoen, "Optimal multiuser spectrum balancing for digital subscriber lines," IEEE Trans.
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