{"@context":"http://iiif.io/api/presentation/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/manifest.json","@type":"sc:Manifest","label":"Part 1. A Study on Delay Tolerant Network Algorithm  for VANET Part 2. An Efficient MU-MIMO Precoding Operation with ZF and MMSE","metadata":[{"label":"dc.description.sponsorship","value":"This work is sponsored by the Stony Brook University Graduate School in compliance with the requirements for completion of degree."},{"label":"dc.format","value":"Monograph"},{"label":"dc.format.medium","value":"Electronic Resource"},{"label":"dc.identifier.uri","value":"http://hdl.handle.net/11401/77442"},{"label":"dc.language.iso","value":"en_US"},{"label":"dc.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.abstract","value":"Part 1. In this paper, we learn how to select the Delay Tolerant Network (DTN) routing protocols according to dynamic network environment in wireless ad hoc network. Basically, providing access to the Internet or other network services with low mobile density is quite difficult for disconnection and long delay. One of the solutions in this problem is using Vehicular Ad-hoc Networks (VANET) with DTN. There are a variety of DTNs, relying on the different network environment. We categorize the DTNs routing protocols. Also, we use simulations to compare that DTN routing protocols lead to reduce end-to-end delay and higher message delivery ratio. For example, Epidemic takes disadvantages in terms of longer delay time and many bundle duplicate copies in high node density. It can lead into collisions and retransmissions. We simulate Binary Spray and Wait, and ProPHET (Probability routing protocol using history of encounters and transitivity) which has shorter delay time and less duplicated bundle receipt. We used the Network Simulator 2 (NS-2) to implement DTN protocols as Epidemic, Binary Spray and Wait and ProPHET to compare in different network environments. This simulation result presents that which routing protocol gives better performance. Part 2. Multi-user multiple-input multiple-output (MU-MIMO) system provides higher capacity gain if the transmitter knows the channel state information (CSI). Precoding techniques require each antenna to transmit a pre-coded data. Particularly, the precoding techniques such as zero forcing (ZF) and minimum mean square error (MMSE) have been provided  for optimal capacity in the system. In this paper, we compare the capacity based on different antennas numbers with ZF and MMSE. We apply the two types of precoding to multiple antennas, considering MU-MIMO downlink with varying number of users. The optimal precoding scheme is different depending on the relative relationship between the transmitter number and the receiver number. The simulation results demonstrate that different combinations of transmitting and receiving antennas have different effect on the capacity. Based on the observations from the simulation results, we propose adaptive precoding scheme for down link (DL) transmissions in order to achieve the capacity-approaching performance  in different operational  environments."},{"label":"dcterms.available","value":"2017-09-20T16:52:42Z"},{"label":"dcterms.contributor","value":"Ye, Fan"},{"label":"dcterms.creator","value":"LYU, TAEK KEUN"},{"label":"dcterms.dateAccepted","value":"2017-09-20T16:52:42Z"},{"label":"dcterms.dateSubmitted","value":"2017-09-20T16:52:42Z"},{"label":"dcterms.description","value":"Department of Electrical Engineering"},{"label":"dcterms.extent","value":"75 pg."},{"label":"dcterms.format","value":"Application/PDF"},{"label":"dcterms.identifier","value":"http://hdl.handle.net/11401/77442"},{"label":"dcterms.issued","value":"2016-12-01"},{"label":"dcterms.language","value":"en_US"},{"label":"dcterms.provenance","value":"Made available in DSpace on 2017-09-20T16:52:42Z (GMT). No. of bitstreams: 1\nLYU_grad.sunysb_0771M_13007.pdf: 1482650 bytes, checksum: 42ffd6e1f2fe3654a76466e433fc21bc (MD5)\n  Previous issue date:    1"},{"label":"dcterms.publisher","value":"The Graduate School, Stony Brook University: Stony Brook, NY."},{"label":"dcterms.subject","value":"Electrical engineering"},{"label":"dcterms.title","value":"Part 1. A Study on Delay Tolerant Network Algorithm  for VANET Part 2. An Efficient MU-MIMO Precoding Operation with ZF and MMSE"},{"label":"dcterms.type","value":"Thesis"},{"label":"dc.type","value":"Thesis"}],"description":"This manifest was generated dynamically","viewingDirection":"left-to-right","sequences":[{"@type":"sc:Sequence","canvases":[{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json","@type":"sc:Canvas","label":"Page 1","height":1650,"width":1275,"images":[{"@type":"oa:Annotation","motivation":"sc:painting","resource":{"@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/13%2F78%2F61%2F137861001824353314095262721173731474552/full/full/0/default.jpg","@type":"dctypes:Image","format":"image/jpeg","height":1650,"width":1275,"service":{"@context":"http://iiif.io/api/image/2/context.json","@id":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/13%2F78%2F61%2F137861001824353314095262721173731474552","profile":"http://iiif.io/api/image/2/level2.json"}},"on":"https://repo.library.stonybrook.edu/cantaloupe/iiif/2/canvas/page-1.json"}]}]}]}