IOSR Journal of Electronics and Communication Engineering (IOSR-JECE) e-ISSN: 2278-2834,p- ISSN: 2278-8735.Volume 15, Issue 2, Ser. II (Mar-Apr 2020), PP 20-22 www.iosrjournals.org DOI: 10.9790/2834-1502022022 www.iosrjournals.org 20 | Page A Survey of User Selection and Sum Rate Maximization Sreeshma M Satheesh 1 , Roselin Raju 2 1 (Department of Electronics and Communication Engineering, Mar Baselios College of Engineering and Technology, Thiruvananthapuram, Kerala, India) 2 (Department of Electronics and Communication Engineering, Mar Baselios College of Engineering and Technology, Thiruvananthapuram, Kerala, India) Abstract:A cellular network is a communication network.Sumrate maximization is an important factor associated with cellular communication. Basically in cellular communication systems downlink is modelled as broadcast channel which includes one base station and several users, where the base station can transmit data to many user. Lots of resource allocation policies are available to achieve maximum sum rate in broadcast channel.This paper includes different techniques and summaries about the sum rate maximization. The major problem in cellular communication system is the active user selection. Selecting active users among many users is a complex optimization problem. Key Words: User selection,Sumratemaximization,MIMO, MIMO-BC --------------------------------------------------------------------------------------------------------------------------------------- Date of Submission: 25-04-2020 Date of Acceptance: 08-05-2020 --------------------------------------------------------------------------------------------------------------------------------------- I. Introduction Wireless communication systems are used to transmit data through a wireless medium over long or short distances. Basically telecommunication systems includes different techniques that are fixed, mobile, and portable two way radios. The most advanced and efficient wireless technologies are Global Positioning System(GPS),satellite television and cordless telephones. In conventional wireless communication systems single antennas are used at both transmit and receive sections. In many cases some critical issues will created due to the single antenna usage at both transmit and receive antennas. To avoid the issues due to the single antenna usage new technology developed is Multiple Input and Multiple Output(MIMO),where multiple number of antennas are present in both transmit and receive section. MIMO is one of the good form of smart antenna technologies, other technologies are MISO(Multiple Input Single Output),SIMO (Single Input Multiple Output). Basically MIMO systems are used to obtain very high data rate over wireless network. Most of the resource allocation policies are used for maximize the achievable sumrate over communication systems. Most commonresource used in communication systems is Power. Power allocation plays an important role in data transmission over wireless networks. Here can introduce Multiple Access Channel(MAC) and MAC-BC Duality theory[2] in order to improve the sum rate. Normally MAC are used for transmit data through more than two terminals which is connected to the same transmission path to improve the system capacity. From several studies obtained a valid result that the Gaussian MAC and BC are duels of each other and provides capacity region of the Broadcast channel and Multiple Access Channel. While considering the Broadcast channel there will only has a single power constraint on every transmitter section. According to” MAC-BC Duality theory”there exists the MAC-BC conversion between the resource distributions in MAC and BC such that the maximumattainable rate tuples are the same while the total power is conserved. Here the Multi output BC can be solved by using iterative water filling technique. Users power allocation changes will affects the interference towards the others in order to avoid this issue the users need to iteratively update their own powers, this effect is called iterative water filling[15]. Consider another optimization problem which is called sum rate maximization problem due to user selection. Here can predict that sum rate of a communication system can be improved by selecting active users[1]. II. Literature Review Multiple Input Multiple Output systems have already evidenced its capability to attain high data rate over various different transmission paths. MIMO BC includes base station with number of multiple antennas which are connects with many users. The important term that associated with the sum rate maximization is multi user diversity gain which says that when hugenumberofusers are available on a communication network ,then the base station canincrease the sumrate by choosing best user subset. According to the studies in recent years there has been excessiveattention in capacity region calculations. Calculating the capacity of Multiple Input Multiple Output broadcast channels, is a key problem due to the absence of a theoretical concept on non- degradedtransmissions. By applying the “dirty paper”coding at the transmitter side can achieve set of