Titlebook: Distributed Space-Time Coding; Yindi Jing Book 2013 The Author(s) 2013 Channel Estimation.Cooperative Network.Diversity Order.Relay Networ

muscle-fibers

Overthrow

狂亂

出來(lái)

Distributed Space-Time Coding for Multiple-Antenna Multiple-Relay Network,transmitter, the receiver, or a relay) is equipped with a single antenna. In this chapter, DSTC is used for ., where each node in the network can be equipped with multiple antennas. At first, the multiple-antenna multiple-relay network model is specified in Sect.?.. Then the DSTC scheme, its diversi

CLAP

Training and Training-Based Distributed Space-Time Coding,n reality, training and channel estimations need to be conducted to obtain the required CSI at the receiver. The estimated CSI is then used in the data transmission. This chapter is on channel training and training-based DSTC. First, the training and estimation of the global and individual channels

埋伏

Distributed Space-Time Coding,ce analysis of DSTC, including the pairwise error probability (PEP) calculations and the diversity order derivation, is also provided. Some code designs for DSTC are introduced in Sect.?.. Finally, in Sect.?., simulated error probabilities of DSTC for several network scenarios are illustrated.

linguistics

嘴唇可修剪

https://doi.org/10.1057/9780230270756ty order analysis, and code design are demonstrated in Sect.?.. After that, the combination of DSTC and maximum-ratio combining (MRC) is explained in Sect.?.. Finally, simulated error probabilities of some multiple-antenna multiple-relay networks are shown.

強(qiáng)化

The British Commonwealth of Nationsof the relay network are considered in Sect.?.. Then, training-based DSTC, i.e, DSTC with estimated CSI, is studied in Sect.?.. After that, the training and estimation of the end-to-end channels for single-antenna relay network and multiple-antenna relay network are explained in Sects.?. and ., respectively.

GREEN

Book 2013c concept of DSTC, its achievable performance, generalizations, code design, and differential use. Recent results on training design and channel estimation for DSTC and the performance of training-based DSTC are also discussed.