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Spectral Efficiency Analysis for Bidirectional Dynamic Network With Massive MIMO Under Imperfect CSI
- Source :
- IEEE Access, Vol 6, Pp 43660-43671 (2018)
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- To cope with the exploding demand for higher data rate and the heavier asymmetry of downlink (DL) and uplink (UL) traffic, dynamic time-division duplex (DTDD) has been proposed, where the time resources can be adjusted dynamically between DL and UL transmission. However, the strict synchronization requirements in DTDD bring extra overhead. In this paper, a bidirectional dynamic network (BDN) with massive multiple input multiple output is studied, in which DL and UL transmission can occur simultaneously. Under imperfect channel-state information, the closed-form expressions for the UL achievable rates with maximum ratio combination (MRC) and zero-forcing (ZF) receivers as well as the DL achievable rates with maximum ratio transmission (MRT) and ZF beamforming are derived in both BDN and DTDD systems. Based on these expressions, we compare the spectral efficiency of BDN and DTDD systems. Numerical results show that the simulation results match well with the closed-form expressions in both BDN and DTDD systems. Furthermore, BDN is more spectral efficient than DTDD. ZF achieves better performance in spectral efficiency than MRC and MRT.
- Subjects :
- Beamforming
Dynamic network analysis
General Computer Science
Computer science
05 social sciences
MIMO
General Engineering
Duplex (telecommunications)
imperfect CSI
050801 communication & media studies
020206 networking & telecommunications
02 engineering and technology
Spectral efficiency
Topology
spectral efficiency
0508 media and communications
Telecommunications link
massive MIMO
0202 electrical engineering, electronic engineering, information engineering
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
Imperfect
Bidirectional dynamic network
lcsh:TK1-9971
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....0630e258a8e578136ceb501d7f40fd14