scholarly journals User Selection and Precoding Techniques for Rate Maximization in Broadcast MISO Systems

10.5772/58937 ◽  
2014 ◽  
Author(s):  
Eduardo Castañeda ◽  
Adão Silva ◽  
Atilio Gameiro
Keyword(s):  
User Selection ◽  
Rate Maximization

scholarly journals Low-Complexity User Selection for Rate Maximization in MIMO Broadcast Channels with Downlink Beamforming

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Eduardo Castañeda ◽  
Adão Silva ◽  
Ramiro Samano-Robles ◽  
Atílio Gameiro
Keyword(s):  
Null Space ◽  
Low Complexity ◽  
Broadcast Channels ◽  
Selection Problem ◽  
Maximization Problem ◽  
User Selection ◽  
Downlink Beamforming ◽  
Rate Maximization ◽  
Sum Rate ◽  
Mimo Broadcast Channels

We present in this work a low-complexity algorithm to solve the sum rate maximization problem in multiuser MIMO broadcast channels with downlink beamforming. Our approach decouples the user selection problem from the resource allocation problem and its main goal is to create a set of quasiorthogonal users. The proposed algorithm exploits physical metrics of the wireless channels that can be easily computed in such a way that a null space projection power can be approximated efficiently. Based on the derived metrics we present a mathematical model that describes the dynamics of the user selection process which renders the user selection problem into an integer linear program. Numerical results show that our approach is highly efficient to form groups of quasiorthogonal users when compared to previously proposed algorithms in the literature. Our user selection algorithm achieves a large portion of the optimum user selection sum rate (90%) for a moderate number of active users.

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

A New Multi-user Selection Algorithm in MIMO Broadcast System with Limited Feedback

2010 ◽  
Vol 32 (11) ◽  
pp. 2785-2789
Author(s):  
Fang Xie ◽  
Chao-wei Yuan ◽  
Tie-zheng Cheng ◽  
Lin Li
Keyword(s):  
Limited Feedback ◽  
User Selection ◽  
Selection Algorithm

Combined User and Antenna Selection in Massive MIMO Using Precoding Technique

2019 ◽  
Vol 9 (2) ◽  
pp. 214-223 ◽  
Author(s):  
Tasher Ali Sheikh ◽  
Joyatri Bora ◽  
Md. Anwar Hussain
Keyword(s):  
Massive Mimo ◽  
Antenna Selection ◽  
Orthogonality Condition ◽  
Channel Gain ◽  
User Selection ◽  
Selection Algorithm

Background and Objectives: We propose here joint semi-orthogonal user selection and antenna selection algorithm based on precoding scheme. Methods: The focus of this proposed algorithm is to increase the system sumrate and decrease the complexity. We select and schedule users from a large number of users based on semi-orthogonality condition among them. Here, we select only the maximum channel gain antennas to maximize the system sumrate. Subsequently, the user selection and antenna selection have been scheduled in an adequate manner in order to obtain maximum system sumrate. We calculate the system sumrate for two scenarios: firstly, by considering the interference and secondly without considering the interference. We achieve maximum system sumrate at MMSE and lowest at without precoding while considering the interference. However, when we do not consider the interference we obtain lowest sumrate at MMSE and maximum at without precoding. Results and Conclusion: Here, we apply the precoding scheme to increase the system sumrate and we obtain approximately 20% to 35% higher system sumrate compared to without precoding, when interference is considered. Thus, we achieve higher sumrate in our proposed algorithms compared to other existing work.

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