Title
Uplink Waveform Channel With Imperfect Channel State Information and Finite Constellation Input
Abstract
This paper investigates the capacity limit of an uplink waveform channel assuming imperfect channel state information at the receiver (CSIR). Various realistic assumptions are incorporated into the problem, which make the study valuable for performance assessment of real cellular networks to identify potentials for performance improvements in practical receiver designs. We assume that the continuous-time received signal is first discretized by mismatched filtering based on the imperfect CSIR. The resulting discrete-time signals are then decoded considering two different decoding strategies, i.e., an optimal decoding strategy based on specific statistics of channel estimation errors and a sub-optimal decoding strategy treating the estimation error signal as additive Gaussian noise. Motivated by the proposed decoding strategies, we study the performance of the decision feedback equalizer for finite constellation inputs, in which inter-stream interferences are treated either using their true statistics or as Gaussian noise. Numerical results are provided to exemplify the benefit of exploiting the knowledge on the statistics of the channel estimation errors and inter-stream interferences. Simulations also assess the effect of the CSI imperfectness on the achievable rate, which reveal that finite constellation inputs are less sensitive to the estimation accuracy than Gaussian input, especially in the high SNR regime.
Year
DOI
Venue
2017
10.1109/TWC.2016.2638420
IEEE Trans. Wireless Communications
Keywords
Field
DocType
Receivers,Channel estimation,Decoding,Estimation error,Uplink,Decision feedback equalizers,Channel capacity
Computer science,Waveform,Algorithm,Communication channel,Filter (signal processing),Real-time computing,Gaussian,Decoding methods,Statistics,Gaussian noise,Channel capacity,Telecommunications link
Journal
Volume
Issue
ISSN
16
2
1536-1276
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Tan Tai Do1286.05
Tobias J. Oechtering238761.82
Su Min Kim312919.92
Mikael Skoglund41397175.71
Gunnar Peters5214.39