FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2909623256> ?p ?o ?g. }

• W2909623256 abstract "Multiple-input multiple-output (MIMO) antenna system is considered as a core technology for wireless communication. To reap the benefits of MIMO at a greater scale, massive MIMO with very large antenna arrays deployed at base station (BS) has recently become the forefront in wireless communication research. Till present, the design and analysis of large-scale MIMO systems is a fairly new subject. On the other hand, excessive power usage in MIMO networks is a crucial issue for mobile operators and the explosive growth of wireless services contributes largely to the worldwide carbon footprint. As such, significant efforts have been devoted to improve the spectral efficiency (SE) as well as energy efficiency (EE) of MIMO communication systems over the past decade, resulting in many energy efficient techniques such as power allocation. This thesis investigates novel energy-efficient pilot-data power control strategies which can be used in both conventional MIMO and massive MIMO communication systems. The new pilot-data power control algorithms are developed based ontwo optimization frameworks: one aims to minimize the total transmit power while satisfying per-user signal-interference-plus-noise ratio (SINR) and power constraints; the other aims to maximize the total EE, which is defined as the ratio of the total SE to the transmit power, under individual user power constraints. The proposed novel pilot-data power allocation schemes also take into account the maximum-ratio combining (MRC) and zero-forcing (ZF) detectors in the uplink together with maximum-ratio transmission (MRT) and ZF precoder in the downlink.Considering that a direct use of such SINR expressions in the power control schemeswould lead to a very difficult optimization problem which is not mathematically tractable, we first investigatethe statistical SINR lower bounds for multi-cell multi-user MIMO (MU-MIMO)communication systemsunder minimum mean square error (MMSE) channel estimation. These lower bounds of the per-user average SINRs are used to replace the true SINRs to simplify the power allocation optimization problems. Such relaxation of the original average SINR yields a simplified problem and leads to a suboptimal solution.Then, based on the derived average SINR lower bounds, two novel energy efficient pilot-data power control problems are formulatedwithin the first optimization framework,aiming to minimize the total transmit power budget subject to the per-user SINR requirement and power consumption constraint in multi-cell MU-MIMO systems. For the EE-optimal power allocation problems with MRT precoder and MRC detector, it is revealed that such minimization problems can be converted to a standard geometric programming (GP) procedure which can be further converted to a convex optimization problem. For the pilot-data power control scheme with ZF precoder and ZF detector, geometric inequality is used to approximate the original non-convex optimization to GP problem. The very large number of BS station situation is also discussed by assuming infinite antennas at BS. Numerical results validate the tightness of the derived SINR lower bounds and the advantages of the proposed energy efficient power allocation schemes.Next, two pilot and data power control schemes are developed based on the second power allocation optimization framework to jointly maximize the total EE for both uplink and downlink transmissions in multi-cell MU-MIMO systems under per-user and BS power constraints. The original power control problems are simplified to equivalent convex problems based on the derived SINR lower bounds along with the Dinkelbach's method and the FrankWolfe (FW) iteration. By assuming infinite antennas at BS, the pilot-data power control in massive MIMO case is also discussed. The performance of the proposed pilot-data power allocation schemes based on the two frameworks, namely total transmit power minimization and total EE maximization, are evaluated and compared with the SE maximization scheme.Furthermore, we investigate the pilot-data power allocation for EE communications in single-cell MU-MIMO systems with circuit power consumption in consideration. The pilot and data power allocation schemes are proposed to minimize the total weighted uplink and downlink transmit power as well as processing circuit power consumption while meeting the per-user SINR and BS power consumption constraints. In our proposed schemes, both fixed and flexible numbers of BS antennas are investigated. For the fixed number of BS antennas case, the non-convex optimization problems are converted to a general GP problem to facilitate the solution. An iterative algorithm is proposed to solve the EE-optimal power control problems in the flexible number of BS antennas casebased on the partial convexity of both the cost function and the constraints. It is shown that the convergence of the proposed iterative algorithm is guaranteed due to the fact that each iteration follows convex optimization." @default.
• W2909623256 created "2019-01-25" @default.
• W2909623256 creator A5082117229 @default.
• W2909623256 date "2018-07-15" @default.
• W2909623256 modified "2023-09-24" @default.
• W2909623256 title "Energy-Efficient Pilot-Data Power Control in MU-MIMO Communication Systems" @default.
• W2909623256 cites W1503954184 @default.
• W2909623256 cites W1515886242 @default.
• W2909623256 cites W1531134412 @default.
• W2909623256 cites W1568721963 @default.
• W2909623256 cites W1573224314 @default.
• W2909623256 cites W1654832238 @default.
• W2909623256 cites W1967029328 @default.
• W2909623256 cites W1967956032 @default.
• W2909623256 cites W1971443733 @default.
• W2909623256 cites W1973977831 @default.
• W2909623256 cites W1979905340 @default.
• W2909623256 cites W1983293748 @default.
• W2909623256 cites W1986468408 @default.
• W2909623256 cites W1988510398 @default.
• W2909623256 cites W1997581312 @default.
• W2909623256 cites W1997988602 @default.
• W2909623256 cites W1999833500 @default.
• W2909623256 cites W2000239511 @default.
• W2909623256 cites W2001382966 @default.
• W2909623256 cites W2017190463 @default.
• W2909623256 cites W2019012533 @default.
• W2909623256 cites W2022341009 @default.
• W2909623256 cites W2023404060 @default.
• W2909623256 cites W2023535408 @default.
• W2909623256 cites W2025262567 @default.
• W2909623256 cites W2031132992 @default.
• W2909623256 cites W2068749191 @default.
• W2909623256 cites W2072184935 @default.
• W2909623256 cites W2084304524 @default.
• W2909623256 cites W2091944925 @default.
• W2909623256 cites W2097850831 @default.
• W2909623256 cites W2098563066 @default.
• W2909623256 cites W2099068206 @default.
• W2909623256 cites W2101051097 @default.
• W2909623256 cites W2103972037 @default.
• W2909623256 cites W2105225341 @default.
• W2909623256 cites W2105872425 @default.
• W2909623256 cites W2106929598 @default.
• W2909623256 cites W2108256297 @default.
• W2909623256 cites W2110080881 @default.
• W2909623256 cites W2117014495 @default.
• W2909623256 cites W2119009551 @default.
• W2909623256 cites W2119952207 @default.
• W2909623256 cites W2120686080 @default.
• W2909623256 cites W2124757599 @default.
• W2909623256 cites W2129733867 @default.
• W2909623256 cites W2130134073 @default.
• W2909623256 cites W2133019626 @default.
• W2909623256 cites W2133111418 @default.
• W2909623256 cites W2136697855 @default.
• W2909623256 cites W2137248065 @default.
• W2909623256 cites W2140462745 @default.
• W2909623256 cites W2140516799 @default.
• W2909623256 cites W2141658588 @default.
• W2909623256 cites W2141682101 @default.
• W2909623256 cites W2142485717 @default.
• W2909623256 cites W2145013959 @default.
• W2909623256 cites W2146742258 @default.
• W2909623256 cites W2154319347 @default.
• W2909623256 cites W2158099801 @default.
• W2909623256 cites W2160998689 @default.
• W2909623256 cites W2163829469 @default.
• W2909623256 cites W2164631123 @default.
• W2909623256 cites W2166873702 @default.
• W2909623256 cites W2168655991 @default.
• W2909623256 cites W2171048418 @default.
• W2909623256 cites W2181303654 @default.
• W2909623256 cites W2255882906 @default.
• W2909623256 cites W2275974491 @default.
• W2909623256 cites W2309773735 @default.
• W2909623256 cites W2405725842 @default.
• W2909623256 cites W2407603800 @default.
• W2909623256 cites W2418350050 @default.
• W2909623256 cites W2500703336 @default.
• W2909623256 cites W2520873811 @default.
• W2909623256 cites W2940016297 @default.
• W2909623256 cites W2963151934 @default.
• W2909623256 cites W2964121147 @default.
• W2909623256 cites W2015563778 @default.
• W2909623256 hasPublicationYear "2018" @default.
• W2909623256 type Work @default.
• W2909623256 sameAs 2909623256 @default.
• W2909623256 citedByCount "0" @default.
• W2909623256 crossrefType "dissertation" @default.
• W2909623256 hasAuthorship W2909623256A5082117229 @default.
• W2909623256 hasConcept C119599485 @default.
• W2909623256 hasConcept C121332964 @default.
• W2909623256 hasConcept C127162648 @default.
• W2909623256 hasConcept C127413603 @default.
• W2909623256 hasConcept C138660444 @default.
• W2909623256 hasConcept C163258240 @default.
• W2909623256 hasConcept C165650700 @default.
• W2909623256 hasConcept C207987634 @default.
• W2909623256 hasConcept C24326235 @default.

• next