Spatial Multiplexing in Random Wireless Networks

2009 ◽  
Author(s):  
Kostas Stamatiou ◽  
John G. Proakis ◽  
James R. Zeidler
Keyword(s):  
Wireless Networks ◽  
Spatial Multiplexing

Transmission capacities for overlaid wireless networks with spatial multiplexing

2012 ◽  
Author(s):  
Xianling Wang ◽  
Xin Zhang ◽  
Jian Geng ◽  
Xiaoyi Liu ◽  
Dacheng Yang
Keyword(s):  
Wireless Networks ◽  
Spatial Multiplexing

Multi-Antenna Spatial Multiplexing in Overlaid Wireless Networks: Transmission Capacity Analysis

2013 ◽  
Vol E96.B (7) ◽  
pp. 1997-2004 ◽  
Author(s):  
Xianling WANG ◽  
Xin ZHANG ◽  
Hongwen YANG ◽  
Dacheng YANG
Keyword(s):  
Wireless Networks ◽  
Spatial Multiplexing ◽  
Transmission Capacity ◽  
Capacity Analysis

scholarly journals Scheduling for Multi-User Multi-Input Multi-Output Wireless Networks with Priorities and Deadlines

2019 ◽  
Vol 11 (8) ◽  
pp. 172
Author(s):  
Li-on Raviv ◽  
Amir Leshem
Keyword(s):  
Wireless Networks ◽  
Mimo Systems ◽  
State Of The Art ◽  
Spatial Multiplexing ◽  
Queue Management ◽  
Ample Evidence ◽  
Data Packets ◽  
Time Frequency ◽  
Management Techniques ◽  
Overall Performance

The spectral efficiency of wireless networks can be significantly improved by exploiting spatial multiplexing techniques known as multi-user MIMO. These techniques enable the allocation of multiple users to the same time-frequency block, thus reducing the interference between users. There is ample evidence that user groupings can have a significant impact on the performance of spatial multiplexing. The situation is even more complex when the data packets have priority and deadlines for delivery. Hence, combining packet queue management and beamforming would considerably enhance the overall system performance. In this paper, we propose a combination of beamforming and scheduling to improve the overall performance of multi-user MIMO systems in realistic conditions where data packets have both priority and deadlines beyond which they become obsolete. This method dubbed Reward Per Second (RPS), combines advanced matrix factorization at the physical layer with recently-developed queue management techniques. We demonstrate the merits of the this technique compared to other state-of-the-art scheduling methods through simulations.

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