語系:
繁體中文
English
說明(常見問題)
回圖書館首頁
手機版館藏查詢
登入
回首頁
切換:
標籤
|
MARC模式
|
ISBD
Resource allocation strategies for c...
~
Nguyen, Diep Ngoc.
FindBook
Google Book
Amazon
博客來
Resource allocation strategies for cognitive and cooperative MIMO communications: Algorithm and protocol design.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Resource allocation strategies for cognitive and cooperative MIMO communications: Algorithm and protocol design./
作者:
Nguyen, Diep Ngoc.
面頁冊數:
185 p.
附註:
Source: Dissertation Abstracts International, Volume: 74-09(E), Section: B.
Contained By:
Dissertation Abstracts International74-09B(E).
標題:
Engineering, Electronics and Electrical. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3563217
ISBN:
9781303113789
Resource allocation strategies for cognitive and cooperative MIMO communications: Algorithm and protocol design.
Nguyen, Diep Ngoc.
Resource allocation strategies for cognitive and cooperative MIMO communications: Algorithm and protocol design.
- 185 p.
Source: Dissertation Abstracts International, Volume: 74-09(E), Section: B.
Thesis (Ph.D.)--The University of Arizona, 2013.
Dynamic Spectrum Access (DSA) and multi-input multi-output (MIMO) communications are among the most promising solutions to address the ever-increasing wireless demand. Cognitive radio (CR) is the enabling technology for DSA. In this dissertation, we propose several resource allocation strategies for multiuser and cooperative MIMO communications in the context of DSA/CR systems and wireless sensor networks (WSNs). First, to maximize the Cognitive MIMO (CMIMO) network throughput, we develop a low-complexity distributed algorithm that configures the transmit antenna radiation directions and allocates power to all data streams over both frequency and space/antenna dimensions. We formulate the joint power, spectrum allocation, and MIMO beamforming problem as a noncooperative game. We prove that the game always admits at least one Nash Equilibrium (NE). To improve the efficiency of this NE (i.e., network throughput), we derive user-dependent pricing policies that force MIMO transmitters to steer their beams away from nearby unintended receivers. Second, we propose beamforming games (with and without pricing policies) that jointly improve the power and spectrum efficiency while meeting various rate demands. We derive sufficient conditions under which a given rate-demand profile can be supported. To account for user fairness, we develop a channel assignment and power allocation mechanism based on the Nash Bargaining solution. The proposed scheme allows CMIMO links to first propose their rate demands, and then cooperate and bargain in the process of determining their channel assignment, power allocation, and "precoding" matrices. In the context of WSNs where energy efficiency is a key design metric, we propose a cooperative MIMO framework. The framework partitions a WSN into various clusters in which several single-antenna sensors cooperate and form a virtual MIMO node so as to conserve power through harvesting MIMO's diversity gain. Extensive simulations show that our proposed schemes achieve significant throughput and energy efficiency improvement compared with state-of-the-art designs.
ISBN: 9781303113789Subjects--Topical Terms:
626636
Engineering, Electronics and Electrical.
Resource allocation strategies for cognitive and cooperative MIMO communications: Algorithm and protocol design.
LDR
:03024nam a2200277 4500
001
1958917
005
20140512081850.5
008
150210s2013 ||||||||||||||||| ||eng d
020
$a
9781303113789
035
$a
(MiAaPQ)AAI3563217
035
$a
AAI3563217
040
$a
MiAaPQ
$c
MiAaPQ
100
1
$a
Nguyen, Diep Ngoc.
$3
2094162
245
1 0
$a
Resource allocation strategies for cognitive and cooperative MIMO communications: Algorithm and protocol design.
300
$a
185 p.
500
$a
Source: Dissertation Abstracts International, Volume: 74-09(E), Section: B.
500
$a
Adviser: Marwan Krunz.
502
$a
Thesis (Ph.D.)--The University of Arizona, 2013.
520
$a
Dynamic Spectrum Access (DSA) and multi-input multi-output (MIMO) communications are among the most promising solutions to address the ever-increasing wireless demand. Cognitive radio (CR) is the enabling technology for DSA. In this dissertation, we propose several resource allocation strategies for multiuser and cooperative MIMO communications in the context of DSA/CR systems and wireless sensor networks (WSNs). First, to maximize the Cognitive MIMO (CMIMO) network throughput, we develop a low-complexity distributed algorithm that configures the transmit antenna radiation directions and allocates power to all data streams over both frequency and space/antenna dimensions. We formulate the joint power, spectrum allocation, and MIMO beamforming problem as a noncooperative game. We prove that the game always admits at least one Nash Equilibrium (NE). To improve the efficiency of this NE (i.e., network throughput), we derive user-dependent pricing policies that force MIMO transmitters to steer their beams away from nearby unintended receivers. Second, we propose beamforming games (with and without pricing policies) that jointly improve the power and spectrum efficiency while meeting various rate demands. We derive sufficient conditions under which a given rate-demand profile can be supported. To account for user fairness, we develop a channel assignment and power allocation mechanism based on the Nash Bargaining solution. The proposed scheme allows CMIMO links to first propose their rate demands, and then cooperate and bargain in the process of determining their channel assignment, power allocation, and "precoding" matrices. In the context of WSNs where energy efficiency is a key design metric, we propose a cooperative MIMO framework. The framework partitions a WSN into various clusters in which several single-antenna sensors cooperate and form a virtual MIMO node so as to conserve power through harvesting MIMO's diversity gain. Extensive simulations show that our proposed schemes achieve significant throughput and energy efficiency improvement compared with state-of-the-art designs.
590
$a
School code: 0009.
650
4
$a
Engineering, Electronics and Electrical.
$3
626636
650
4
$a
Engineering, System Science.
$3
1018128
690
$a
0544
690
$a
0790
710
2
$a
The University of Arizona.
$b
Electrical and Computer Engineering.
$3
2094163
773
0
$t
Dissertation Abstracts International
$g
74-09B(E).
790
$a
0009
791
$a
Ph.D.
792
$a
2013
793
$a
English
856
4 0
$u
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3563217
筆 0 讀者評論
館藏地:
全部
電子資源
出版年:
卷號:
館藏
1 筆 • 頁數 1 •
1
條碼號
典藏地名稱
館藏流通類別
資料類型
索書號
使用類型
借閱狀態
預約狀態
備註欄
附件
W9253745
電子資源
11.線上閱覽_V
電子書
EB
一般使用(Normal)
在架
0
1 筆 • 頁數 1 •
1
多媒體
評論
新增評論
分享你的心得
Export
取書館
處理中
...
變更密碼
登入