MAXIMUM TRANSMISSION DISTANCE OF GEOGRAPHIC TRANSMISSIONS ON RAYLEIGH CHANNELS
|
|
- Irene Lane
- 5 years ago
- Views:
Transcription
1 MAXIMUM TRANSMISSION DISTANCE OF GEOGRAPHIC TRANSMISSIONS ON RAYLEIGH CHANNELS Tathagata D. Goswami and John M. Shea Wireless Information Networking Group, 458 ENG Building #33 P.O. Box 63 University of Florida Abstract We consider the use of multiuser diversity to maximize transmission distance in a wireless network. This differs from previous work on multiuser diversity, which focused mainly on increasing the data rate. We analyze the maximum achievable transmission distance in a geocasting scenario, in which any radio in a specified geographical area is an acceptable destination for a packet. Performance results are presented for Rayleigh fading and nonfading channels. To illustrate the benefits of multiuser diversity, we show that higher transmission distances can be achieved over fading channels than over nonfading channels if the density of radios is sufficiently high. We also illustrate one application of our results to protocol design. I. INTRODUCTION In wireless networks, more than one of the neighbors of the transmitter may be an acceptable receiver for a message. For instance, in multi-hop wireless ad hoc networks, radios act as routers to direct packets from the source to the destination. The goal is for the message to reach the destination in an efficient manner. Since there may be many alternative routes available between any source-destination pair, there are many possibilities for intermediate radios between the source and destination. If the channels are changing because of multipath fading, then the neighbors of a radio may change over time even when the positions of the radios have not significantly changed the topology of the network. Techniques to adapt to these channel changes by exploiting the alternative acceptable receivers are called multi-user diversity techniques. Originally multiuser diversity was proposed for application to cellular networks,. Later, however it was investigated for ad hoc networks in 3, 4. In an ad hoc network, the choice of next-hop receiver for a packet is usually determined by a routing algoritm according to various cost metrics. As early as 984, Takagi and Kleinrock proposed routing protocols based on the locations of the nodes in the network 4. The importance of geographic routing geocasting) was well established in 5 where the authors implement an application layer scheme overlayed on the network layer to transport a message to all geographically distributed users. Geographic routing in mobile adhoc networks is based on a multihop packet forwarding mechanism according to which a radio forwards a source packet to one greedy forwarding) or more restricted directional flooding) neighbors of the source according to their location with respect to the source and destination 6. Several geographic routing protocols have been proposed in the literature cf. 7, 6 and references therein). Our work is similar to that on Geographic Random Forwarding GeRaF) 8 in which the authors investigate the use of geographic transmission to route packets in the presence of unknown sleep schedules. Under the GeRaF protocol, when a radio has a packet to send it broadcasts to all radios in the coverage area. Those radios which listen to the transmission will act as intermediate relays), depending on its/their distance from the destination. Finally the authors study the multihop performance of their protocol, in terms of the average number of hops it takes for a packet to reach the destination and the average number of available neighbors. In 8, the authors consider that two neighbors can communicate when they are within the coverage radius of each other. This model although simplistic, fails to capture the propagation in a practical wireless environment. In this work, we focus on a single transmission interval, and we anaylze the performance with random fading channels. Most previous work on geographic transmission focuses on the design of the routing protocol when a specific destination is known. In this work, we focus on a single-hop and analyze the statistics of the maximum distance that can be achieved from the transmitter to a group of receivers. This scenario may arise in several applications. In certain sensor networks 9, a sensing node near the middle of a monitored area must relay their information toward collection nodes around the edges of the area. Previous work on transmission range in wireless networks focussed more on adjusting transmission power in the absence of fading to improve throughput or control network connectivitycf., 3, 4, 5). In fact, 4 showed that the expected progress per transmission is proportional to the transmission radius. In 6, the optimum transmission range was obtained from a graph theoretic point. In 7, the channel model used was based on some fixed parameters and did not account for random fading. In 8, a random graph theoretic framework was used to obtain the critical power required when the number of nodes is large. This paper is organized as follows. The system model considered is presented in Section II, and our analytical results are detailed in Section III. Performance results and an application to protocol design are presented in Section IV, and conclusions are given in Section V. II. SYSTEM MODEL We study a broadcast communication environment in which a single source radio transmitter) transmits information to
2 mean. Without loss of generality, the SNR at node i can be modeled as! " % $ Fig.. Geographic region considered in the analysis: sector of angle θ of an annular ring with interior radius R and exterior radius R.! # Y i = h i X n i, 3) where n denotes the path-loss exponent. We assume n which is reasonable outside a small neighborhood of the transmitting antenna. We compare the performance of the system with Rayleigh fading to the performance with nonfading AWGN channels. For this scenario, the SNR Y i at the receiver at the end of a transmission, depends only on the random distance X i from the transmitter and can thus be modeled as Y i = X n i. 4) destination radios receivers) that are distributed around the source radio according to a Poisson point process in a twodimensional plane at rate λ radios per unit area. We first consider a sector of angle θ of an annular ring with inner radius R, outer radius R, as shown in Fig.. The probability that there are l radios inside the sector is given by P L = l = exp λa)λa)l, l =,..., ) l! where A = πr R)θ/π) is the area of the sector. Under the Poisson point process, the receivers within such an annular sector are distributed uniform in area, and hence the distribution function for the distance to an arbitrary receiver is given by, x R x F Xi x) = R, R R < x R ) R, x > R. A. Transmission Model We consider transmission in the wireless environment using a fading channel model and a nonfading AWGN channel model. We consider the AWGN channel model to determine in which scenarios) fading can actually improve the transmission distance when multiuser diversity is used. We assume that all radios in the system use identical, omni-directional antennas. A transmission over a single hop is considered successful if the signal-to-noise ratio SNR) at the receiver is greater than or equal to a receiver sensitivity, ρ which we assume is identical for all receivers. We consider a slowly varying, flat Rayleigh fading channel. We also assume that the channel fading gains are constant over each period during which a message is transmitted from a source radio, and we assume that the fading gains are independent between nodes. Thus, the signal power received at an arbitrary mobile receiver depends only on the distance between the base station and that receiver and the fading gain at the receiver during that transmission. Let X i denote the distance from the transmitter to node i and let α i denote the Rayleigh fading coefficient for node i. Then h i = α i is an exponential random variable with III. ANALYSIS A. Maximum Transmission Distance We first consider transmission into a sector of an annular ring, as described in the previous section. A radio can successfully recover a message if Y i ρ, or X i h i /ρ) /n. Again, without loss of generality, we let ρ = and define V i = X i I, h ni X i ), 5) where I A.) is the indicator function given by, x A I A x) =, otherwise. That is, V i = X i if the receiver can successfully recover the message and V i = otherwise. Then conditioned on N randomly located radios in the sector, the maximum distance M to a receiver that can successfully recover a message from the transmitter can be expressed as maxv, V... V N }, N =,... M = 6), N =. Thus, from 6), the conditional distribution of M given that there are N radios in the network is given by F Vi v) N, v F M v N) = 7), v < for N =,,.... We have derived F Vi v) in the Appendix for the Rayleigh fading channel to be F V v) = exp R n ) + v R R exp v n ) R + R γ + n ), R vn γ + ) n, Rn +Rexp v n ) exp R n )} for v R, R, R > R. In the above derivation, γa, x) is the incomplete Gamma function γa, x) = x t a exp t)dt,
3 3 Γa) is the Gamma function Γa) = t a exp t)dt, Note that this derivation can be trivially modified to obtain F Vi v) for the nonfading AWGN channel, i.e. h i = ), for which V i = if X i >. Now suppose that the receivers around the transmitter are Poisson distributed in two-dimensional space at rate λ nodes per unit area and the transmission is intended only for radios in an annular sector of area A. Then for v, the distribution of the maximum transmission range, F M v), can be easily obtained from 7) and ) as F M v) = E N F Vi v) N = exp λaf Vi v) λa). 8) For v <, F M v) =. We shall now extend our analysis of the maximum transmission range to infinite networks, assuming that the source is at the origin and that all the radios in the network are awake, i.e R, R. Consider a sequence of random variables M, M, M 3... M i... where M R denotes the maximum transmission range when the radius is R. Let F Mi t) denote the cumulative distribution function of the random variable M i. Let F M t) = lim i F Mi t). Then if the limit exists, M is a random variable with distribution function F M, and the sequence of random variables M i } converges to M in distribution. ) Fading channel model: Putting R =, R = R in the expression for F Vi v) derived in the Appendix and substituting the resulting expression in 8) yields F MR t) = exp λ θ γ + n ), tn + t exp t n ) γ + n ) ), Rn R exp R n ) = exp λθ ) n Γ n, tn, 9) where the last line follows after applying the properties of the incomplete gamma function. The normalized node density λ is defined as the expected number of radios within a circle of radius unity, which is given by, λ = λ θ. Thus, we can rewrite 9) as F M t) = exp λ ) n Γ /n, tn ) ) ) Nonfading channel model: In the AWGN channel, all the radios within a circle of radius unity are able to receive the message correctly. Hence the distribution function of M as R, can be easily derived to be, F M t) = exp λ θ t )), t <, otherwise ) Similar to the fading channel, we have replaced the node density λ with the normalized node density, λ = λ θ. Thus, we can rewrite ) as, exp λ t )), t < F M t) = ), otherwise The expected value of the maximum transmission range for both the fading and nonfading channels is given by, E M = F M x) dx. 3) Since we have not found a closed form expression for this expected value, we have obtained this value numerically. Note that the distribution function for the nonfading channel given by ) does not depend on the path loss exponent n whereas the distribution function for the Rayleigh fading channel given by ) is dependent on n. Thus the expected value of the maximum transmission range for the nonfading channel does not depend on the exponential path loss. B. Outage probability and critical distance for the infinitely large network In many scenarios, it would be desirable that the message at least travel some minimum distance. I.e., we desire that the furthest receiver to successfully recover the message be at least some critical distance d c from the transmitter. We define the outage probability P out, as the probability that the limiting transmission range M is less than d c. Thus, for d c >, we have F M d c ) = P out 4) It is very important to note that the distribution of the limiting transmission range M for both the Rayleigh fading and the nonfading channel model has some mass at zero. I.e., F M d = ). This is in part because there is some nonzero probability that there are no receivers in the network. Thus when there are no receivers in the network, there is some nonzero probability that the broadcast transmission remained at the transmitter. Hence, while choosing the value of P out for d c >, we must be careful to obey the bound given by, P out exp λ n Γ n )) for the fading channel model and P out exp λ ) for the AWGN channel model. We next obtain the expression for d c for the fading and AWGN channel models. ) Fading channel model: For d c > and P out exp λ n Γ n)), by equating ) and 4), we have, exp λ ) n Γ /n, tn ) = P out Taking log on both sides and after some simplification, we end up having to solve the following integral equation for d c, Γ n, dn c ) = n λ log /P out ) 5) We mention here that 5) admits solutions for the path loss exponent n =, 4. We have tight bounds for n = 3, but omit
4 4 them because of length limitations. Case : n = Putting n = on both sides of 5), we have Γ, d c) = λ log /P out ) exp d ) c = log /P out ) λ d c = log λ log /P out ) Case : n = 4 Putting n = 4 on both sides of 5), we have Γ, d4 c) = log /P out ) λ Fig.. Expected Value of the Maximum transmission range vs. the t normalized node density exp t)dt = log /P out ) d λ 4 c ) π erfc d 4 c = log /P out ).6 λ ).4 d c = erfc log /P out ) λ π. where erfc.) is the complementary error function given by erfcx) = exp t ) dt π ) Nonfading channel model: For < d c and exp λ ) P out <, by equating ) and 4), we have, exp λ d c )) = P out d c = x IV. RESULTS + λ log P out In this section, we present results on the expected value of the normalized maximum transmission range, which is found by taking the expected value over the distributions given by ) or ). Here, normalized indicates that we have normalized the maximum transmission range for the AWGN channel to.. So, unit of normalized distance corresponds to the transmission radius of the AWGN channel. We also plot with respect to normalized node density, which is the expected value of the number of radios that lie within that normalized transmission radius. We have plotted the expected value of the normalized maximum transmission range given by 3) vs. the normalized node density in Fig.. For the AWGN channel, the transmission range achieved saturates to the maximum transmission range of as the number of nodes in that transmission range increases. The expected value of the achieved transmission range for the fading channels is larger than for the AWGN channels because of multiuser diversity. With as few as six average neighbors, fading channels along with multiuser diversity results in an increase in the average transmission distance of 5%, 5%, and 87.5% over the distance on the AWGN channel for path-loss exponents of 4, 3, and, respectively. Expected value of Max. transmission range d c.5.5 fading n=) fading n=3) fading n=4) no fading Normalized node density λ fading no fading Normalized node density λ Fig. 3. Critical distance of transmission vs. average number of radios for an outage probability of.5, for a path loss exponent n = To further evaluate the benefits of multiuser diversity, we consider transmission in fading and nonfading channels in terms of the critical transmission distance d c. The results in Figs. 3 and 4 show the normalized critical transmission distance for path loss exponents n = and 4. We have plotted these values by considering an outage probability of 5%. When n =, for radios in the network, 95% of the time, fading improves the critical transmission distance by a factor of.375. Similarly, the diversity gain when there are radios and n = 4 is.9. Note that this indicates that if there are radios in the network, then the nonfading channel outperforms the fading channel. Thus, there is a break-even point in terms of the normalized radio density, after which fading with multiuser diversity outperforms the nonfading channel. We have plotted the break-even points for a range of values of the pathloss exponent n in Fig. 5, for an outage probability of.5. Fig. 5 also indicates the region in which transmission in fading channel is better than the nonfading channel to overcome pathloss and vice versa. Fading offers the best performance in the region above the curve, and nonfading in the region below.
5 5 d c fading no fading Normalized node density λ region with interior and exterior radii given by d c and d c, respectively. We have compared our protocol with a simpler dumb protocol that transmits to all receivers within a circular transmission radius R d from the transmitter. For a fair comparison between the two protocols, we limit this transmission radius R d such that the average number of radios within d c and d c are the same as that within a circle of radius R d. We compare these two protocols based on the expected value of the maximum transmission range and the probability that not even a single receiver within the transmission range receives a message from the transmitter correctly. We provide results for α =.95 and path loss exponent n = 4. Fig. 4. Critical distance of transmission vs. average number of radios for an outage probability of.5, for a path loss exponent n = 4 Normalized node density λ Average Max. transmission range α protocol dumb protocol Normalized node density λ Path loss exponent n Fig. 6. Expected Value of the Maximum transmission range vs. the normalized node density for a path loss exponent n = 4 Fig. 5. Region marking zones of operation for fading and nonfading channel for an outage probability of.5 Routing Protocol We demonstrate the utility of our analytical results in protocol design by considering the design of a sleeping protocol. We do not claim that this protocol is in any sense optimal, but it does demonstrate how our results can be useful. Consider the receivers distributed in an infinitely large plane around the transmitter according to a Poisson process with normalized node density λ, i.e λ is the average number of radios inside a circle of unit radius. Our protocol limits the number of radios that must turn on to those that are most likely to be at the maximum reception distance. To do this, we sacrifice some reliability in the sense that limiting the set of radios that turn on may occasionally decrease the maximum transmission distance that can be achieved or may cause the message to not be successfully received by any radio. We state that our protocol is α-reliable if we limit the receivers that turn on according to, F M d c M > ) = α 6) F M d c M > ) = + α. Then we limit the radios that turn on to those within an annular Prob. not recd. message correctly 3 α protocol dumb protocol Normalized Node density λ Fig. 7. Probability that not even a single receiver in the transmission range received the message correctly, for a path loss exponent n = 4 The expected value of the maximum transmission range is shown in Fig. 6. Clearly, the α-reliable performs better than the dumb protocol in transmitting the message further. This is because for the dumb protocol, too many radios turn on that are usually short of the maximum transmission distance. The values of P Rx) for various λ is plotted in Fig. 7 on a semilog scale. We see that we are introducing some cost in our α-reliable protocol in that we increase the probability that none
6 6 of the receivers successfully recovers the message. However, as the receivers in these cases are close to the transmitter, this is generally not a significant loss. V. CONCLUSION AND FUTURE WORK In this paper, we derived the distribution function of the maximum transmission distance achievable for a geographic transmission over a channel exposed to exponential path loss and Rayleigh fading. We used this distribution function to obtain the critical transmission range, given some outage probability. We provide expressions for the critical transmission range for path loss exponents n =, 4 and provide tight bounds for n = 3. To obtain the scenarios) where fading is beneficial we also provided results for transmission in a nonfading channel. Our results indicate that when there are a large number of radios in the network, then fading is beneficial to transport the message from the source to the destination. We have also obtained the region of operation, in terms of the normalized node density, when fading overcomes signal loss due to exponential path decay. Though not the focus of this paper, we have provided an example of a very simple routing protocol that utilizes the maximum transmission distance as a metric. APPENDIX F V v) = P V i v) = P X i I v Xi h n i ) = E hi P X i I v Xi h n h i i ) = E hi P X i minv, h n i } h i ) + E hi P X i > h ni h i Substituting into ) yields, ) F V v) = E hi min h n i, v R R R +E hi I min v,h ni + >R ) I R<min v,h n i R h n E i R hi R I + I R R<h n i R h ni >R Now we shall consider the various intervals in which v lies. For v, R, R >, R > R. F V v) = exp R n ) R γ + ) R n, Rn γ + ) n, Rn Rexp R n ) exp R n )} For v R, R, F V v) = exp R n ) + v R R exp v n ) + R ) R R Here, γa, x) is the incomplete Gamma function: γa, x) = x and Γa) is the Gamma function: Γa) = t a exp t)dt t a exp t)dt REFERENCES R. Knopp and P. A. Humblet, Information capacity and power control in single-cell multiuser communications, in Proc. 995 IEEE Int. Conf. Commun., vol., Seattle), pp , June 995. P. Black, M. Grob, R. Padovani, N. Sindhushyana, and S. Viterbi, CDMA/HDR : a bandwidth efficient high speed wireless data service for nomadic users, IEEE Communications Magazine, vol. 38, pp. 7 77, July. 3 P. Larsson, Selection diversity forwarding in a multihop packet radio network with fading channel and capture, in ACM SIGMOBILE Mobile Computing and Communication Review, pp , Oct.. 4 W. H. Wong, J. M. Shea, and T. F. Wong, Cooperative diviersity slotted ALOHA, in Proc. nd Int. Conf on Quality of Service in Heterogeneous Wired/Wireless Networks QShine), Orlando, Florida), pp , Aug J. C. Navas and T. Imielinski, Geocast - geographic addressing and routing, in Proc. of the 3 rd Annual ACM/IEEE Intl. Conf. on Mobile Computing and Networking,MOBICOM 97), M. Mauve, J. Widmer, and H. Hartenstein, A survey on position-based routing in mobile ad hoc networks, IEEE Network Magazine, vol. 5, pp. 3 39, Nov.. 7 I. Stojmenovic, Position-based routing in ad hoc networks, IEEE Commun. Mag., vol. 4, pp. 8 34, Jul. 8 M. Zorzi and R. R. Rao, Geographic random forwarding GeRaF) for ad hoc and sensor networks : Multihop performance, IEEE Trans. Mobile Computing, vol., pp , Oct.-Dec I. F. Akyildiz, W. Su, Y. Sankarsubramaniam, and E.Cayirci, A survey on sensor networks, IEEE Commun. Mag., vol. 4, pp. 4, Aug.. D. C. Verma, Content Distribution Networks, An Engineering Approach. New York: Wiley,. R. R. Choudhury and N. H. Vaidya, Mac-layer anycasting in ad hoc networks, SIGCOMM Comput. Commun. Rev., vol. 34, no., pp. 75 8, 4. L. Kleinrock and J. A. Silvester, Optimum transmission radii for packet radio networks or why six is a magic number, in Proc. Conf. Rec. Nat. Telecommun. Conf, L. Kleinrock and J. A. Silvester, Spatial reuse in multihop packet radio networks, in Proc. IEEE, vol. 75, pp. 6 34, Jan H. Takagi and L. Kleinrock, Optimum transmission ranges for randomly distributed packet radio terminals, IEEE Trans. Commun., vol. 3, pp , Mar T. C. Hou and V. O. K. Li, Transmission range control in multihop packet radio networks, IEEE Trans. Commun, vol. 34, pp , Jan M. Sanchez, P. Manzoni, and Z. Haas, Determination of critical transmission range in adhoc networks, in Proc. of Multiaccess Mobility and Teletraffic for Wireless Communications Workshop MMT 99), J. Deng, Y. S. Han, P. Chen, and P. K. Varshney, Optimum transmission range for wireless ad hoc networks, in Proc. IEEE Wireless Communications and Networking Conf.WCNC 4), 4. 8 P. Gupta and P. R. Kumar, Critical power for asymptotic connectivity, in Proc. IEEE Conf. on Decision and Control, 998. γ + n ), vn γ + ) n, Rn + Rexp v n ) exp R n )}
Energy-Efficient Duty Cycle Assignment for Receiver-Based Convergecast in Wireless Sensor Networks
Energy-Efficient Duty Cycle Assignment for Receiver-Based Convergecast in Wireless Sensor Networks Yuqun Zhang, Chen-Hsiang Feng, Ilker Demirkol, Wendi B. Heinzelman Department of Electrical and Computer
More informationThroughput-optimal number of relays in delaybounded multi-hop ALOHA networks
Page 1 of 10 Throughput-optimal number of relays in delaybounded multi-hop ALOHA networks. Nekoui and H. Pishro-Nik This letter addresses the throughput of an ALOHA-based Poisson-distributed multihop wireless
More informationAn Efficient Cooperation Protocol to Extend Coverage Area in Cellular Networks
An Efficient Cooperation Protocol to Extend Coverage Area in Cellular Networks Ahmed K. Sadek, Zhu Han, and K. J. Ray Liu Department of Electrical and Computer Engineering, and Institute for Systems Research
More informationPerformance of ALOHA and CSMA in Spatially Distributed Wireless Networks
Performance of ALOHA and CSMA in Spatially Distributed Wireless Networks Mariam Kaynia and Nihar Jindal Dept. of Electrical and Computer Engineering, University of Minnesota Dept. of Electronics and Telecommunications,
More informationTransmission Scheduling in Capture-Based Wireless Networks
ransmission Scheduling in Capture-Based Wireless Networks Gam D. Nguyen and Sastry Kompella Information echnology Division, Naval Research Laboratory, Washington DC 375 Jeffrey E. Wieselthier Wieselthier
More informationJoint Relaying and Network Coding in Wireless Networks
Joint Relaying and Network Coding in Wireless Networks Sachin Katti Ivana Marić Andrea Goldsmith Dina Katabi Muriel Médard MIT Stanford Stanford MIT MIT Abstract Relaying is a fundamental building block
More informationMobility and Fading: Two Sides of the Same Coin
1 Mobility and Fading: Two Sides of the Same Coin Zhenhua Gong and Martin Haenggi Department of Electrical Engineering University of Notre Dame Notre Dame, IN 46556, USA {zgong,mhaenggi}@nd.edu Abstract
More informationSUPERPOSITION CODING IN THE DOWNLINK OF CDMA CELLULAR SYSTEMS
SUPERPOSITION ODING IN THE DOWNLINK OF DMA ELLULAR SYSTEMS Surendra Boppana, John M. Shea Wireless Information Networking Group Department of Electrical and omputer Engineering University of Florida 458
More informationStability Analysis for Network Coded Multicast Cell with Opportunistic Relay
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 00 proceedings Stability Analysis for Network Coded Multicast
More informationSuperposition Coding in the Downlink of CDMA Cellular Systems
Superposition Coding in the Downlink of CDMA Cellular Systems Surendra Boppana and John M. Shea Wireless Information Networking Group University of Florida Feb 13, 2006 Outline of the talk Introduction
More informationOptimum Power Allocation in Cooperative Networks
Optimum Power Allocation in Cooperative Networks Jaime Adeane, Miguel R.D. Rodrigues, and Ian J. Wassell Laboratory for Communication Engineering Department of Engineering University of Cambridge 5 JJ
More informationMultihop Routing in Ad Hoc Networks
Multihop Routing in Ad Hoc Networks Dr. D. Torrieri 1, S. Talarico 2 and Dr. M. C. Valenti 2 1 U.S Army Research Laboratory, Adelphi, MD 2 West Virginia University, Morgantown, WV Nov. 18 th, 20131 Outline
More informationBandwidth-SINR Tradeoffs in Spatial Networks
Bandwidth-SINR Tradeoffs in Spatial Networks Nihar Jindal University of Minnesota nihar@umn.edu Jeffrey G. Andrews University of Texas at Austin jandrews@ece.utexas.edu Steven Weber Drexel University sweber@ece.drexel.edu
More informationTransport Capacity and Spectral Efficiency of Large Wireless CDMA Ad Hoc Networks
Transport Capacity and Spectral Efficiency of Large Wireless CDMA Ad Hoc Networks Yi Sun Department of Electrical Engineering The City College of City University of New York Acknowledgement: supported
More informationEffects of Beamforming on the Connectivity of Ad Hoc Networks
Effects of Beamforming on the Connectivity of Ad Hoc Networks Xiangyun Zhou, Haley M. Jones, Salman Durrani and Adele Scott Department of Engineering, CECS The Australian National University Canberra ACT,
More informationCalculation of the Spatial Reservation Area for the RTS/CTS Multiple Access Scheme
Calculation of the Spatial Reservation Area for the RTS/CTS Multiple Access Scheme Chin Keong Ho Eindhoven University of Technology Elect. Eng. Depart., SPS Group PO Box 513, 56 MB Eindhoven The Netherlands
More informationOn the Optimal SINR in Random Access Networks with Spatial Reuse
On the Optimal SINR in Random ccess Networks with Spatial Reuse Navid Ehsan and R. L. Cruz Department of Electrical and Computer Engineering University of California, San Diego La Jolla, C 9293 Email:
More informationOn Multiple Users Scheduling Using Superposition Coding over Rayleigh Fading Channels
On Multiple Users Scheduling Using Superposition Coding over Rayleigh Fading Channels Item Type Article Authors Zafar, Ammar; Alnuweiri, Hussein; Shaqfeh, Mohammad; Alouini, Mohamed-Slim Eprint version
More informationOpportunistic cooperation in wireless ad hoc networks with interference correlation
Noname manuscript No. (will be inserted by the editor) Opportunistic cooperation in wireless ad hoc networks with interference correlation Yong Zhou Weihua Zhuang Received: date / Accepted: date Abstract
More informationIN recent years, there has been great interest in the analysis
2890 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 52, NO. 7, JULY 2006 On the Power Efficiency of Sensory and Ad Hoc Wireless Networks Amir F. Dana, Student Member, IEEE, and Babak Hassibi Abstract We
More informationDynamic Power Allocation for Multi-hop Linear Non-regenerative Relay Networks
Dynamic ower llocation for Multi-hop Linear Non-regenerative Relay Networks Tingshan Huang, Wen hen, and Jun Li Department of Electronics Engineering, Shanghai Jiaotong University, Shanghai, hina 224 {ajelly
More informationTransmit Power Allocation for BER Performance Improvement in Multicarrier Systems
Transmit Power Allocation for Performance Improvement in Systems Chang Soon Par O and wang Bo (Ed) Lee School of Electrical Engineering and Computer Science, Seoul National University parcs@mobile.snu.ac.r,
More informationInformation Theory at the Extremes
Information Theory at the Extremes David Tse Department of EECS, U.C. Berkeley September 5, 2002 Wireless Networks Workshop at Cornell Information Theory in Wireless Wireless communication is an old subject.
More informationSimple, Optimal, Fast, and Robust Wireless Random Medium Access Control
Simple, Optimal, Fast, and Robust Wireless Random Medium Access Control Jianwei Huang Department of Information Engineering The Chinese University of Hong Kong KAIST-CUHK Workshop July 2009 J. Huang (CUHK)
More informationTHROUGHPUT AND CHANNEL CAPACITY OF MULTI-HOP VIRTUAL CELLULAR NETWORK
The th International Symposium on Wireless Personal Multimedia Communications (MC 9) THOUGHPUT AND CHANNEL CAPACITY OF MULTI-HOP VITUAL CELLULA NETWO Eisuke udoh Tohoku University Sendai, Japan Fumiyuki
More informationSENSOR PLACEMENT FOR MAXIMIZING LIFETIME PER UNIT COST IN WIRELESS SENSOR NETWORKS
SENSOR PACEMENT FOR MAXIMIZING IFETIME PER UNIT COST IN WIREESS SENSOR NETWORKS Yunxia Chen, Chen-Nee Chuah, and Qing Zhao Department of Electrical and Computer Engineering University of California, Davis,
More informationOn the Transmission Capacity of Wireless Multi-Channel Ad Hoc Networks with local FDMA scheduling
On the Transmission Capacity of Wireless Multi-Channel Ad Hoc Networks with local FDMA scheduling Jens P. Elsner, Ralph Tanbourgi and Friedrich K. Jondral Karlsruhe Institute of Technology, Germany {jens.elsner,
More informationPerformance Analysis of Energy Consumption of AFECA in Wireless Sensor Networks
Proceedings of the World Congress on Engineering 2 Vol II WCE 2, July 6-8, 2, London, U.K. Performance Analysis of Energy Consumption of AFECA in Wireless Sensor Networks Yun Won Chung Abstract Energy
More informationSPECTRUM SHARING IN CRN USING ARP PROTOCOL- ANALYSIS OF HIGH DATA RATE
Int. J. Chem. Sci.: 14(S3), 2016, 794-800 ISSN 0972-768X www.sadgurupublications.com SPECTRUM SHARING IN CRN USING ARP PROTOCOL- ANALYSIS OF HIGH DATA RATE ADITYA SAI *, ARSHEYA AFRAN and PRIYANKA Information
More informationSpace-Time Coded Cooperative Multicasting with Maximal Ratio Combining and Incremental Redundancy
Space-Time Coded Cooperative Multicasting with Maximal Ratio Combining and Incremental Redundancy Aitor del Coso, Osvaldo Simeone, Yeheskel Bar-ness and Christian Ibars Centre Tecnològic de Telecomunicacions
More informationScaling Laws of Cognitive Networks
Scaling Laws of Cognitive Networks Mai Vu, 1 Natasha Devroye, 1, Masoud Sharif, and Vahid Tarokh 1 1 Harvard University, e-mail: maivu, ndevroye, vahid @seas.harvard.edu Boston University, e-mail: sharif@bu.edu
More informationOpportunistic Communication in Wireless Networks
Opportunistic Communication in Wireless Networks David Tse Department of EECS, U.C. Berkeley October 10, 2001 Networking, Communications and DSP Seminar Communication over Wireless Channels Fundamental
More informationA survey on broadcast protocols in multihop cognitive radio ad hoc network
A survey on broadcast protocols in multihop cognitive radio ad hoc network Sureshkumar A, Rajeswari M Abstract In the traditional ad hoc network, common channel is present to broadcast control channels
More informationA New Analysis of the DS-CDMA Cellular Uplink Under Spatial Constraints
A New Analysis of the DS-CDMA Cellular Uplink Under Spatial Constraints D. Torrieri M. C. Valenti S. Talarico U.S. Army Research Laboratory Adelphi, MD West Virginia University Morgantown, WV June, 3 the
More informationCapacity and Cooperation in Wireless Networks
Capacity and Cooperation in Wireless Networks Chris T. K. Ng and Andrea J. Goldsmith Stanford University Abstract We consider fundamental capacity limits in wireless networks where nodes can cooperate
More informationA Geometric Interpretation of Fading in Wireless Networks: Theory and Applications Martin Haenggi, Senior Member, IEEE
5500 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 54, NO 12, DECEMBER 2008 A Geometric Interpretation of Fading in Wireless Networks: Theory Applications Martin Haenggi, Senior Member, IEEE Abstract In
More informationRevisiting Neighbor Discovery with Interferences Consideration
Author manuscript, published in "3rd ACM international workshop on Performance Evaluation of Wireless Ad hoc, Sensor and Ubiquitous Networks (PEWASUN ) () 7-1" DOI : 1.115/1131.1133 Revisiting Neighbor
More informationPerformance Analysis of Cooperative Communication System with a SISO system in Flat Fading Rayleigh channel
Performance Analysis of Cooperative Communication System with a SISO system in Flat Fading Rayleigh channel Sara Viqar 1, Shoab Ahmed 2, Zaka ul Mustafa 3 and Waleed Ejaz 4 1, 2, 3 National University
More informationScaling Laws of Cognitive Networks
Scaling Laws of Cognitive Networks Invited Paper Mai Vu, 1 Natasha Devroye, 1, Masoud Sharif, and Vahid Tarokh 1 1 Harvard University, e-mail: maivu, ndevroye, vahid @seas.harvard.edu Boston University,
More informationCONSIDER THE following power capture model. If
254 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 45, NO. 2, FEBRUARY 1997 On the Capture Probability for a Large Number of Stations Bruce Hajek, Fellow, IEEE, Arvind Krishna, Member, IEEE, and Richard O.
More informationRandom access on graphs: Capture-or tree evaluation
Random access on graphs: Capture-or tree evaluation Čedomir Stefanović, cs@es.aau.dk joint work with Petar Popovski, AAU 1 Preliminaries N users Each user wants to send a packet over shared medium Eual
More informationOptimal Power Allocation over Fading Channels with Stringent Delay Constraints
1 Optimal Power Allocation over Fading Channels with Stringent Delay Constraints Xiangheng Liu Andrea Goldsmith Dept. of Electrical Engineering, Stanford University Email: liuxh,andrea@wsl.stanford.edu
More informationRandomized Channel Access Reduces Network Local Delay
Randomized Channel Access Reduces Network Local Delay Wenyi Zhang USTC Joint work with Yi Zhong (Ph.D. student) and Martin Haenggi (Notre Dame) 2013 Joint HK/TW Workshop on ITC CUHK, January 19, 2013 Acknowledgement
More informationCooperative Routing in Wireless Networks
Cooperative Routing in Wireless Networks Amir Ehsan Khandani Jinane Abounadi Eytan Modiano Lizhong Zheng Laboratory for Information and Decision Systems Massachusetts Institute of Technology 77 Massachusetts
More informationRouting versus Network Coding in Erasure Networks with Broadcast and Interference Constraints
Routing versus Network Coding in Erasure Networks with Broadcast and Interference Constraints Brian Smith Department of ECE University of Texas at Austin Austin, TX 7872 bsmith@ece.utexas.edu Piyush Gupta
More informationOpportunistic Routing in Wireless Mesh Networks
Opportunistic Routing in Wireless Mesh Networks Amir arehshoorzadeh amir@ac.upc.edu Llorenç Cerdá-Alabern llorenc@ac.upc.edu Vicent Pla vpla@dcom.upv.es August 31, 2012 Opportunistic Routing in Wireless
More informationCooperative Diversity Routing in Wireless Networks
Cooperative Diversity Routing in Wireless Networks Mostafa Dehghan, Majid Ghaderi, and Dennis L. Goeckel Department of Computer Science, University of Calgary, Emails: {mdehghan, mghaderi}@ucalgary.ca
More informationAmplify-and-Forward Space-Time Coded Cooperation via Incremental Relaying Behrouz Maham and Are Hjørungnes
Amplify-and-Forward Space-Time Coded Cooperation via Incremental elaying Behrouz Maham and Are Hjørungnes UniK University Graduate Center, University of Oslo Instituttveien-5, N-7, Kjeller, Norway behrouz@unik.no,
More informationSimulcast Packet Transmission in Ad Hoc Networks
Simulcast Packet Transmission in Ad Hoc Networks Kiung Jung and John M. Shea Wireless Information Networking Group Department of Electrical and Computer Engineering University of Florida Gainesville, FL
More informationPower Controlled Random Access
1 Power Controlled Random Access Aditya Dua Department of Electrical Engineering Stanford University Stanford, CA 94305 dua@stanford.edu Abstract The lack of an established infrastructure, and the vagaries
More informationSuperposition Coding Based Cooperative Communication with Relay Selection
Superposition Coding Based Cooperative Communication with Relay Selection Hobin Kim, Pamela C. Cosman and Laurence B. Milstein ECE Dept., University of California at San Diego, La Jolla, CA 9093 Abstract
More informationTHE EFFECT of multipath fading in wireless systems can
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 47, NO. 1, FEBRUARY 1998 119 The Diversity Gain of Transmit Diversity in Wireless Systems with Rayleigh Fading Jack H. Winters, Fellow, IEEE Abstract In
More informationELEC E7210: Communication Theory. Lecture 11: MIMO Systems and Space-time Communications
ELEC E7210: Communication Theory Lecture 11: MIMO Systems and Space-time Communications Overview of the last lecture MIMO systems -parallel decomposition; - beamforming; - MIMO channel capacity MIMO Key
More informationOpportunistic Beamforming Using Dumb Antennas
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 48, NO. 6, JUNE 2002 1277 Opportunistic Beamforming Using Dumb Antennas Pramod Viswanath, Member, IEEE, David N. C. Tse, Member, IEEE, and Rajiv Laroia, Fellow,
More informationChapter 10. User Cooperative Communications
Chapter 10 User Cooperative Communications 1 Outline Introduction Relay Channels User-Cooperation in Wireless Networks Multi-Hop Relay Channel Summary 2 Introduction User cooperative communication is a
More informationAchieving Low Outage Probability with Network Coding in Wireless Multicarrier Multicast Systems
Achieving Low Outage Probability with Networ Coding in Wireless Multicarrier Multicast Systems Juan Liu, Wei Chen, Member, IEEE, Zhigang Cao, Senior Member, IEEE, Ying Jun (Angela) Zhang, Senior Member,
More informationOn the Performance of Cooperative Routing in Wireless Networks
1 On the Performance of Cooperative Routing in Wireless Networks Mostafa Dehghan, Majid Ghaderi, and Dennis L. Goeckel Department of Computer Science, University of Calgary, Emails: {mdehghan, mghaderi}@ucalgary.ca
More informationDynamic Subchannel and Bit Allocation in Multiuser OFDM with a Priority User
Dynamic Subchannel and Bit Allocation in Multiuser OFDM with a Priority User Changho Suh, Yunok Cho, and Seokhyun Yoon Samsung Electronics Co., Ltd, P.O.BOX 105, Suwon, S. Korea. email: becal.suh@samsung.com,
More informationABSTRACT. Ahmed Salah Ibrahim, Doctor of Philosophy, 2009
ABSTRACT Title of Dissertation: RELAY DEPLOYMENT AND SELECTION IN COOPERATIVE WIRELESS NETWORKS Ahmed Salah Ibrahim, Doctor of Philosophy, 2009 Dissertation directed by: Professor K. J. Ray Liu Department
More informationAnalysis of Bottleneck Delay and Throughput in Wireless Mesh Networks
Analysis of Bottleneck Delay and Throughput in Wireless Mesh Networks Xiaobing Wu 1, Jiangchuan Liu 2, Guihai Chen 1 1 State Key Laboratory for Novel Software Technology, Nanjing University, China wuxb@dislab.nju.edu.cn,
More informationAvoid Impact of Jamming Using Multipath Routing Based on Wireless Mesh Networks
Avoid Impact of Jamming Using Multipath Routing Based on Wireless Mesh Networks M. KIRAN KUMAR 1, M. KANCHANA 2, I. SAPTHAMI 3, B. KRISHNA MURTHY 4 1, 2, M. Tech Student, 3 Asst. Prof 1, 4, Siddharth Institute
More informationOptimal Threshold Scheduler for Cellular Networks
Optimal Threshold Scheduler for Cellular Networks Sanket Kamthe Fachbereich Elektrotechnik und Informationstechnik TU Darmstadt Merck str. 5, 683 Darmstadt Email: sanket.kamthe@stud.tu-darmstadt.de Smriti
More informationFREQUENCY DOUBLE REUSE FOR INDOOR AND URBAN DIGITAL CELLULAR TELEPHONE SYSTEMS ENHANCED CONCEPTUAL DESIGN FORMULAE FOR SINGLE HANDSET SYSTEMS
Reprinted from: Proc. of the 997 Multiaccess, Mobility and Teletraffic for Personal Communications Workshop (MMT 97) FREQUENCY DOUBLE REUSE FOR INDOOR ND URBN DIGITL CELLULR TELEPHONE SYSTEMS ENHNCED CONCEPTUL
More informationTRANSMISSION STRATEGIES FOR SINGLE-DESTINATION WIRELESS NETWORKS
The 20 Military Communications Conference - Track - Waveforms and Signal Processing TRANSMISSION STRATEGIES FOR SINGLE-DESTINATION WIRELESS NETWORKS Gam D. Nguyen, Jeffrey E. Wieselthier 2, Sastry Kompella,
More informationMultihop Relay-Enhanced WiMAX Networks
0 Multihop Relay-Enhanced WiMAX Networks Yongchul Kim and Mihail L. Sichitiu Department of Electrical and Computer Engineering North Carolina State University Raleigh, NC 27695 USA. Introduction The demand
More informationOptimum Threshold for SNR-based Selective Digital Relaying Schemes in Cooperative Wireless Networks
Optimum Threshold for SNR-based Selective Digital Relaying Schemes in Cooperative Wireless Networks Furuzan Atay Onat, Abdulkareem Adinoyi, Yijia Fan, Halim Yanikomeroglu, and John S. Thompson Broadband
More informationAdaptive Resource Allocation in Wireless Relay Networks
Adaptive Resource Allocation in Wireless Relay Networks Tobias Renk Email: renk@int.uni-karlsruhe.de Dimitar Iankov Email: iankov@int.uni-karlsruhe.de Friedrich K. Jondral Email: fj@int.uni-karlsruhe.de
More informationDegrees of Freedom of Multi-hop MIMO Broadcast Networks with Delayed CSIT
Degrees of Freedom of Multi-hop MIMO Broadcast Networs with Delayed CSIT Zhao Wang, Ming Xiao, Chao Wang, and Miael Soglund arxiv:0.56v [cs.it] Oct 0 Abstract We study the sum degrees of freedom (DoF)
More informationDynamic Resource Allocation for Multi Source-Destination Relay Networks
Dynamic Resource Allocation for Multi Source-Destination Relay Networks Onur Sahin, Elza Erkip Electrical and Computer Engineering, Polytechnic University, Brooklyn, New York, USA Email: osahin0@utopia.poly.edu,
More informationStatistical Analysis of MIMO Scheme under Nakagami Fading Channels
Statistical Analysis of MIMO Scheme under Nakagami Fading Channels Nagesh K. N *, Satyanarayana D**, Madhava Prabhu S * and M.N Giri Prasad *** * Middle East College, Knowledge Oasis, Al Rusyal, Sultanate
More informationCRITICAL TRANSMISSION RANGE FOR CONNECTIVITY IN AD-HOC NETWORKS
CHAPTER CRITICAL TRASMISSIO RAGE FOR COECTIVITY I AD-HOC ETWORKS HOSSEI AJORLOO, S. HASHEM MADDAH HOSSEII, ASSER YAZDAI 2, AD ABOLFAZL LAKDASHTI 3 Iran Telecommunication Research Center, Tehran, Iran,
More information4740 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 7, JULY 2011
4740 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 57, NO. 7, JULY 2011 On Scaling Laws of Diversity Schemes in Decentralized Estimation Alex S. Leong, Member, IEEE, and Subhrakanti Dey, Senior Member,
More informationKing Fahd University of Petroleum & Minerals Computer Engineering Dept
King Fahd University of Petroleum & Minerals Computer Engineering Dept COE 543 Mobile and Wireless Networks Term 0 Dr. Ashraf S. Hasan Mahmoud Rm -148-3 Ext. 174 Email: ashraf@ccse.kfupm.edu.sa 4//003
More informationEnd-to-End Known-Interference Cancellation (E2E-KIC) with Multi-Hop Interference
End-to-End Known-Interference Cancellation (EE-KIC) with Multi-Hop Interference Shiqiang Wang, Qingyang Song, Kailai Wu, Fanzhao Wang, Lei Guo School of Computer Science and Engnineering, Northeastern
More informationMedium Access Control via Nearest-Neighbor Interactions for Regular Wireless Networks
Medium Access Control via Nearest-Neighbor Interactions for Regular Wireless Networks Ka Hung Hui, Dongning Guo and Randall A. Berry Department of Electrical Engineering and Computer Science Northwestern
More informationCoordination-free Repeater Groups in Wireless Sensor Networks Andreas Willig
Technical University Berlin Telecommunication Networks Group Coordination-free Repeater Groups in Wireless Sensor Networks Andreas Willig awillig@tkn.tu-berlin.de Berlin, August 2006 TKN Technical Report
More informationSmart Scheduling and Dumb Antennas
Smart Scheduling and Dumb Antennas David Tse Department of EECS, U.C. Berkeley September 20, 2002 Berkeley Wireless Research Center Opportunistic Communication One line summary: Transmit when and where
More informationENERGY EFFICIENT SENSOR NODE DESIGN IN WIRELESS SENSOR NETWORKS
Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology IJCSMC, Vol. 3, Issue. 4, April 2014,
More informationMULTIPATH fading could severely degrade the performance
1986 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 53, NO. 12, DECEMBER 2005 Rate-One Space Time Block Codes With Full Diversity Liang Xian and Huaping Liu, Member, IEEE Abstract Orthogonal space time block
More information3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 53, NO. 10, OCTOBER 2007
3432 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL 53, NO 10, OCTOBER 2007 Resource Allocation for Wireless Fading Relay Channels: Max-Min Solution Yingbin Liang, Member, IEEE, Venugopal V Veeravalli, Fellow,
More informationAchievable Transmission Capacity of Cognitive Radio Networks with Cooperative Relaying
Achievable Transmission Capacity of Cognitive Radio Networks with Cooperative Relaying Xiuying Chen, Tao Jing, Yan Huo, Wei Li 2, Xiuzhen Cheng 2, Tao Chen 3 School of Electronics and Information Engineering,
More informationIntroduction. Introduction ROBUST SENSOR POSITIONING IN WIRELESS AD HOC SENSOR NETWORKS. Smart Wireless Sensor Systems 1
ROBUST SENSOR POSITIONING IN WIRELESS AD HOC SENSOR NETWORKS Xiang Ji and Hongyuan Zha Material taken from Sensor Network Operations by Shashi Phoa, Thomas La Porta and Christopher Griffin, John Wiley,
More informationUtility-optimal Cross-layer Design for WLAN with MIMO Channels
Utility-optimal Cross-layer Design for WLAN with MIMO Channels Yuxia Lin and Vincent W.S. Wong Department of Electrical and Computer Engineering The University of British Columbia, Vancouver, BC, Canada,
More informationDownlink Erlang Capacity of Cellular OFDMA
Downlink Erlang Capacity of Cellular OFDMA Gauri Joshi, Harshad Maral, Abhay Karandikar Department of Electrical Engineering Indian Institute of Technology Bombay Powai, Mumbai, India 400076. Email: gaurijoshi@iitb.ac.in,
More informationEnergy Efficient MAC Protocol with Localization scheme for Wireless Sensor Networks using Directional Antennas
Energy Efficient MAC Protocol with Localization scheme for Wireless Sensor Networks using Directional Antennas Anique Akhtar Department of Electrical Engineering aakhtar13@ku.edu.tr Buket Yuksel Department
More informationThreshold-based Adaptive Decode-Amplify-Forward Relaying Protocol for Cooperative Systems
Threshold-based Adaptive Decode-Amplify-Forward Relaying Protocol for Cooperative Systems Safwen Bouanen Departement of Computer Science, Université du Québec à Montréal Montréal, Québec, Canada bouanen.safouen@gmail.com
More informationAn Overlaid Hybrid-Duplex OFDMA System with Partial Frequency Reuse
An Overlaid Hybrid-Duplex OFDMA System with Partial Frequency Reuse Jung Min Park, Young Jin Sang, Young Ju Hwang, Kwang Soon Kim and Seong-Lyun Kim School of Electrical and Electronic Engineering Yonsei
More informationMobile Base Stations Placement and Energy Aware Routing in Wireless Sensor Networks
Mobile Base Stations Placement and Energy Aware Routing in Wireless Sensor Networks A. P. Azad and A. Chockalingam Department of ECE, Indian Institute of Science, Bangalore 5612, India Abstract Increasing
More informationUnicast Barrage Relay Networks: Outage Analysis and Optimization
Unicast Barrage Relay Networks: Outage Analysis and Optimization S. Talarico, M. C. Valenti, and T. R. Halford West Virginia University, Morgantown, WV. TrellisWare Technologies, nc., San Diego, CA. Oct.
More informationHedonic Coalition Formation for Distributed Task Allocation among Wireless Agents
Hedonic Coalition Formation for Distributed Task Allocation among Wireless Agents Walid Saad, Zhu Han, Tamer Basar, Me rouane Debbah, and Are Hjørungnes. IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. 10,
More informationPERFORMANCE ANALYSIS OF DIFFERENT M-ARY MODULATION TECHNIQUES IN FADING CHANNELS USING DIFFERENT DIVERSITY
PERFORMANCE ANALYSIS OF DIFFERENT M-ARY MODULATION TECHNIQUES IN FADING CHANNELS USING DIFFERENT DIVERSITY 1 MOHAMMAD RIAZ AHMED, 1 MD.RUMEN AHMED, 1 MD.RUHUL AMIN ROBIN, 1 MD.ASADUZZAMAN, 2 MD.MAHBUB
More informationFast and efficient randomized flooding on lattice sensor networks
Fast and efficient randomized flooding on lattice sensor networks Ananth Kini, Vilas Veeraraghavan, Steven Weber Department of Electrical and Computer Engineering Drexel University November 19, 2004 presentation
More informationCoverage and Rate in Finite-Sized Device-to-Device Millimeter Wave Networks
Coverage and Rate in Finite-Sized Device-to-Device Millimeter Wave Networks Matthew C. Valenti, West Virginia University Joint work with Kiran Venugopal and Robert Heath, University of Texas Under funding
More informationWireless Multicasting with Channel Uncertainty
Wireless Multicasting with Channel Uncertainty Jie Luo ECE Dept., Colorado State Univ. Fort Collins, Colorado 80523 e-mail: rockey@eng.colostate.edu Anthony Ephremides ECE Dept., Univ. of Maryland College
More informationCombined Transmitter Diversity and Multi-Level Modulation Techniques
SETIT 2005 3rd International Conference: Sciences of Electronic, Technologies of Information and Telecommunications March 27 3, 2005 TUNISIA Combined Transmitter Diversity and Multi-Level Modulation Techniques
More informationDynamic Frequency Hopping in Cellular Fixed Relay Networks
Dynamic Frequency Hopping in Cellular Fixed Relay Networks Omer Mubarek, Halim Yanikomeroglu Broadband Communications & Wireless Systems Centre Carleton University, Ottawa, Canada {mubarek, halim}@sce.carleton.ca
More informationOPPORTUNISTIC ALOHA AND CROSS LAYER DESIGN FOR SENSOR NETWORKS. Parvathinathan Venkitasubramaniam, Srihari Adireddy and Lang Tong
OPPORTUNISTIC ALOHA AND CROSS LAYER DESIGN FOR SENSOR NETWORKS Parvathinathan Venkitasubramaniam Srihari Adireddy and Lang Tong School of Electrical and Computer Engineering Cornell University Ithaca NY
More informationPerformance study of node placement in sensor networks
Performance study of node placement in sensor networks Mika ISHIZUKA and Masaki AIDA NTT Information Sharing Platform Labs, NTT Corporation 3-9-, Midori-Cho Musashino-Shi Tokyo 8-8585 Japan {ishizuka.mika,
More informationChannel Equalization for STBC-Encoded Cooperative Transmissions with Asynchronous Transmitters
Channel Equalization for STBC-Encoded Cooperative Transmissions with Asynchronous Transmitters Xiaohua(Edward) Li, Fan Ng, Jui-Te Hwu, and Mo Chen Department of Electrical and Computer Engineering State
More informationPacket Error Probability for Decode-and-Forward Cooperative Networks of Selfish Users
Packet Error Probability for Decode-and-Forward Cooperative Networks of Selfish Users Ioannis Chatzigeorgiou 1, Weisi Guo 1, Ian J. Wassell 1 and Rolando Carrasco 2 1 Computer Laboratory, University of
More information