CAPACITY OF UNDERWATER WIRELESS COMMUNICATION CHANNEL WITH DIFFERENT ACOUSTIC PROPAGATION LOSS MODELS

Similar documents
On the Relationship Between Capacity and Distance in an Underwater Acoustic Communication Channel

Effect of Estimation Error on Adaptive L-MRC Receiver over Nakagami-m Fading Channels

BER Performance Analysis of Cognitive Radio Physical Layer over Rayleigh fading Channel

Availability Analysis for Elastic Optical Networks with Multi-path Virtual Concatenation Technique

Co-channel Interference Suppression Techniques for STBC OFDM System over Doubly Selective Channel

ADAPTIVE ITERATION SCHEME OF TURBO CODE USING HYSTERESIS CONTROL

Design and Implementation of Short Range Underwater Acoustic Communication Channel using UNET

Channel Division Multiple Access Based on High UWB Channel Temporal Resolution

Capacity of Data Collection in Arbitrary Wireless Sensor Networks

A Low Complexity VCS Method for PAPR Reduction in Multicarrier Code Division Multiple Access

THE TRADEOFF BETWEEN DIVERSITY GAIN AND INTERFERENCE SUPPRESSION VIA BEAMFORMING IN

Project: IEEE P Working Group for Wireless Personal Area Networks N

COMPARATIVE ANALYSIS OF ULTRA WIDEBAND (UWB) IEEE A CHANNEL MODELS FOR nlos PROPAGATION ENVIRONMENTS

Resource Allocation via Linear Programming for Fractional Cooperation

Theoretical Analysis of Power Saving in Cognitive Radio with Arbitrary Inputs

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1

ENERGY MANAGEMENT OF WIRELESS SENSOR NETWORK WITH MIMO TECHNIQUES

Resource Allocation via Linear Programming for Multi-Source, Multi-Relay Wireless Networks

Utility-Proportional Fairness in Wireless Networks

Performance Measures of a UWB Multiple-Access System: DS/CDMA versus TH/PPM

Estimation and Control of Lateral Displacement of Electric Vehicle Using WPT Information

Open Access The Design of the Acoustic Isolator Used in Acoustic Telemetry While Drilling. Xie Haiming 1,2*, Zhou Jing 2 and Zhang Feng 3

Dealing with Link Blockage in mmwave Networks: D2D Relaying or Multi-beam Reflection?

International Journal of Research in Computer and Communication Technology, Vol 3, Issue 1, January- 2014

Uplink Massive MIMO SIR Analysis: How do Antennas Scale with Users?

FOR energy limited data networks, e.g., sensor networks,

Performance Comparison of Cyclo-stationary Detectors with Matched Filter and Energy Detector M. SAI SINDHURI 1, S. SRI GOWRI 2

PROPORTIONAL FAIR SCHEDULING OF UPLINK SINGLE-CARRIER FDMA SYSTEMS

Joint Optimal Power Allocation and Relay Selection with Spatial Diversity in Wireless Relay Networks

Wireless Communications

Rateless Codes for the Gaussian Multiple Access Channel

Iterative Transceiver Design for Opportunistic Interference Alignment in MIMO Interfering Multiple-Access Channels

CHANNEL MODELLING & PERFORMANCE ANALYSIS OF WIFI

Worst case delay analysis for a wireless point-to-point transmission

Cross-layer queuing analysis on multihop relaying networks with adaptive modulation and coding K. Zheng 1 Y. Wang 1 L. Lei 2 W.

Joint Spectrum Access and Pricing in Cognitive Radio Networks with Elastic Traffic

Coverage and Rate Analysis for Millimeter Wave Cellular Networks

Best Relay Selection Using SNR and Interference Quotient for Underlay Cognitive Networks

Secure Physical Layer Key Generation Schemes: Performance and Information Theoretic Limits

Analyzing Uplink SINR and Rate in Massive. MIMO Systems Using Stochastic Geometry

Sparse Beamforming Design for Network MIMO System with Per-Base-Station Backhaul Constraints

Airborne Ultrasonic Position and Velocity Measurement Using Two Cycles of Linear-Period-Modulated Signal

Spatial Reuse in Dense Wireless Areas: A Cross-layer Optimization Approach via ADMM

RESEARCH OF UHV CIRCUIT BREAKER TRANSIENT RECOVERY VOLTAGE CHARACTERISTIC

Low Delay Wind Noise Cancellation for Binaural Hearing Aids

ES 442 Homework #8 Solutions (Spring 2017 Due May 1, 2017 ) Print out homework and do work on the printed pages.

WIFI-BASED IMAGING FOR GPR APPLICATIONS: FUNDAMENTAL STUDY AND EXPERIMENTAL RESULTS

A CPW-Fed Printed Monopole Ultra-Wideband Antenna with E-Shaped Notched Band Slot

CHANNEL ESTIMATION PERFORMANCE FOR ZERO-OVERHEAD CHANNEL ACCESS IN MOBILE SENSOR NETWORKS

Rate-Allocation Strategies for Closed-Loop MIMO-OFDM

Hybrid Digital-to-Analog Beamforming for Millimeter-Wave Systems with High User Density

On the Relationship Between Queuing Delay and Spatial Degrees of Freedom in a MIMO Multiple Access Channel

A Distributed Utility Max-Min Flow Control Algorithm

The Acoustic Channel and Delay: A Tale of Capacity and Loss

Simulation Model for a Frequency-Selective Land Mobile Satellite Communication Channel

Satellite Link Layer Performance Using Two Copy SR-ARQ and Its Impact on TCP Traffic

DESIGN OF SHIP CONTROLLER AND SHIP MODEL BASED ON NEURAL NETWORK IDENTIFICATION STRUCTURES

INTERNATIONAL TELECOMMUNICATION UNION 02/4%#4)/.!'!).34 ).4%2&%2%.#%

THE EMERGING IEEE ad wireless local area

Proceedings of Meetings on Acoustics

Yongxiang Zhao Brookhaven National Laboratory Upton, NY, July 1998 CENTER FOR ACCELERATOR PHYSICS

Joint Optimization of Scheduling and Power Control in Wireless Networks: Multi-Dimensional Modeling and Decomposition

Model of Neuro-Fuzzy Prediction of Confirmation Timeout in a Mobile Ad Hoc Network

Resource Allocation for Network-Integrated Device-to-Device Communications Using Smart Relays

R is in the unit of ma/mw or A/W. For semiconductor detectors, the value is approximately, 0.5 ma/mw.

Effect of Interfering Users on the Modulation Order and Code Rate for UWB Impulse-Radio Bit-Interleaved Coded M-ary PPM

An Empirical Ultra Wideband Channel Model for Indoor Laboratory Environments

Research Article Dual-Dipole UHF RFID Tag Antenna with Quasi-Isotropic Patterns Based on Four-Axis Reflection Symmetry

Dual Relay Selection for Cooperative NOMA with Distributed Space Time Coding

Secrecy Outage Analysis over Correlated Composite Nakagami-m/Gamma Fading Channels

Relay for Data: An Underwater Race

Energy-Aware Scheduling with Quality of Surveillance Guarantee in Wireless Sensor Networks

Power Control and Transmission Scheduling for Network Utility Maximization in Wireless Networks

3-D BSS Geometric Indicator for WLAN Planning

On optimizing low SNR wireless networks using network coding

Space-Time Focusing Transmission in Ultra-wideband Cooperative Relay Networks

Theoretical Profile of Ring-Spun Slub Yarn and its Experimental Validation

University of Bristol - Explore Bristol Research. Peer reviewed version. Link to published version (if available): /GLOCOM.2003.

Run to Potential: Sweep Coverage in Wireless Sensor Networks

An Optimization Framework for XOR-Assisted Cooperative Relaying in Cellular Networks

Spatial Characteristics of 3D MIMO Wideband Channel in Indoor Hotspot Scenario at 3.5 GHz

Acoustic Propagation Modeling Based on Underwater Wireless Sensor Communication - Research Challenges

Joint Beamforming and Power Optimization with Iterative User Clustering for MISO-NOMA Systems

BVRIT HYDERABAD College of Engineering for Women Department of Electronics and Communication Engineering

Performance Analysis of Non-Orthogonal Multiple Access under I/Q Imbalance

SCHEDULING the wireless links and controlling their

Short Notes Lg Q in the Eastern Tibetan Plateau

Research on a Sea Snake Robot

Communication Systems

Research Article Characterization of Energy Availability in RF Energy Harvesting Networks

Energy-efficient Video Streaming from High-speed Trains

Robust Blind Multiuser Detection in DS-CDMA Systems over Nakagami-m Fading Channels with Impulsive Noise including MRC Receive Diversity

On the Design of Underwater Acoustic Cellular Systems

Hybrid Digital-Analog Joint Source Channel Coding for Broadcast Multiresolution Communications

Distributed Resource Allocation for Relay-Aided Device-to-Device Communication: A Message Passing Approach

CO-ORDINATE POSITION OF SENSOR IN MASS OF CUTTING TOOL

STATISTICAL MODELING OF A SHALLOW WATER ACOUSTIC COMMUNICATION CHANNEL

Distributed Resource Allocation for Relay-Aided Device-to-Device Communication Under Channel Uncertainties: A Stable Matching Approach

An Evaluation of Connectivity in Mobile Wireless Ad Hoc Networks

Minimizing Distribution Cost of Distributed Neural Networks in Wireless Sensor Networks

Transcription:

CAPACITY OF UNDERWATER WIRELESS COMMUNICATION CHANNEL WITH DIFFERENT ACOUSTIC PROPAGATION LOSS MODELS Susan Joshy and A.V. Babu, Department of Eectronics & Communication Engineering, Nationa Institute of Technoogy Caicut, India soosanjoshy@gmai.com, babu@nitc.ac.in ABSTRACT In this paper, we cacuate the capacity of a point-to-point communication ink in an underwater acoustic channe. The anaysis takes into account the effects of various acoustic propagation oss modes. A physica mode of ambient noise power spectra density is aso considered. We perform a comparative assessment of the infuence of various acoustic transmission oss modes on the acoustic bandwidth and the capacity. KEYWORDS Channe Capacity, Optima Bandwidth, Point-to-Point Communication, Underwater Acoustic Channe,. INTRODUCTION Underwater (UW) acoustic networks are generay formed by acousticay connected ocean bottom sensor nodes, autonomous UW vehices, and surface stations that serve as gateways and provide radio communication inks to on-shore stations []. UW acoustic sensor networks consist of sensors and vehices depoyed underwater and networked via acoustic inks to perform coaborative monitoring tasks. However, the acoustic channes impose many constraints that affect the design of UW communication systems. These are characterized by a path oss that depends on both the transmission distance and the signa frequency. The signa frequency determines the absorption oss, which increases with distance as we [, ], eventuay imposing a imit on the avaiabe bandwidth. The Shannon capacity of a channe represents the theoretica upper bound for the maximum rate of data transmission at an arbitrariy sma bit error rate, and is given by the mutua information of the channe maximized over a possibe source distributions. The capacity of a time invariant additive white Gaussian noise (AWGN) channe with bandwidth and SNR is DOI :.5/ijcnc..5 9

og where the capacity achieving source distribution is Gaussian [5]. Authors of [] present numerica soution for the capacity of a very simpe UW acoustic channe without considering its frequency and distance dependant attenuation characteristics. In [], experimenta resuts on channe capacity for a shaow water wave-guide are presented. The capacity anaysis of UW acoustic OFDM based ceuar network is presented in []. In [], author presents the UW capacity based on an acoustic path oss mode and investigates the capacity distance reation. In this paper, the resuts of [] are extended. Based on the statistica and empirica acoustic path oss modes avaiabe in the iterature, we cacuate the capacity of a UW point-to-point ink. We anayze the effects of different propagation phenomena such as surface refection, surface duct, bottom bounce, and other effects such as acoustic absorption and spreading on the capacity.. ACOUSTIC TRANSMISSION LOSS AND AMBIENT NOISE In this section, anaytica modes for UW propagation oss and ambient noise are introduced. Acoustic transmission oss (TL) is the accumuated decrease in acoustic intensity as the sound traves from the source to the receiver.. Absorption and Spreading Loss Acoustic path oss depends on the signa frequency and distance. This dependence is a consequence of absorption (i.e., transfer of acoustic energy into heat). In addition, signa experiences a spreading oss, which increases with distance. Spreading oss refers to the energy distributed over an increasingy arger area due to the reguar weakening of a sound signa as it spreads outwards from the source. The overa transmission oss that occurs in UW channe over a transmission distance of meters at a signa frequency f is given by []: TL = k. og +. og a( f ) () where k is spreading factor ( k = for spherica spreading, k = for cyindrica spreading, and k =.5 for the so-caed practica spreading). In genera, for shaow water channes, cyindrica spreading is assumed ( k = ) whie for deep water channes spherica spreading is assumed ( k = ). Now og a( f ) is the absorption coefficient expressed using Thorp s formua, which gives a ( f ) in db/km for f in khz as foows []: 9

f f + f 4 + f 4 og a( f ) =. + 44 +.75. f +. () The absorption coefficient increases rapidy with frequency, and is a major factor that imits the maxima usabe frequency for an acoustic ink of a given distance. The transmission oss due to absorption and spreading (we refer this case as mode ) is shown in Figure for k =. 5. The oss increases rapidy with frequency and distance, imposing a imit on the avaiabe acoustic bandwidth.. Loss Due to Sound Propagation Characteristics Sound propagates in the sea through many different paths, which depend upon the sound-speed structure in the water as we as the source and receiver ocations. Further, mutipath propagation is affected by depth, frequency and transmission range. In the next sub-sections, we present the transmission oss expressions corresponding to three basic propagation paths between a sourcereceiver pair: surface refection, surface duct, and bottom bounce... Surface Refection Surface refection describes the refection of sound from the sea surface, and is affected by the roughness or smoothness of the sea. When the sea is rough, the transmission oss on refection can be found using the Beckmann-Spizzichino surface refection mode []: TL f + f (9 w) θ = + 6 f + f _ SR og where f = f and f = 78w, where w is the wind speed in knots, and θ is the ange of incidence to the horizonta measured in degrees. The tota acoustic path oss is computed (we refer this case as mode ) using Eqn. (4) beow and is shown in Figure ( w = m/sec, θ = 5 ). () TL = k.og +.og a( f ) + TL _ SR (4).. Surface duct In a surface duct, sound propagates to ong ranges by successive refections from the sea surface aong ray paths that are ong arcs of circes and the corresponding transmission oss, 94

incuding oss due to absorption and spreading is given as foows (we refer this case as mode ) []: TL = k.og +.(og a( f ) + α L ) (5) S 6.6 f (.4) where H is the ayer depth in meters and α L = / [(45 +.5 t) H ]. Here S stands for the sea state number, and t is the temperature. The resuting transmission oss is potted in Figure (assumed parameters are S =, H = 9meters, and t = c )... Bottom bounce This corresponds to the refection of sound from the sea foor. The refection oss of sound incident at a grazing ange θ to a pain boundary between two fuids of density ρ and ρ and of sound veocity c and c is given by the ratio of intensity of the refected wave I r reated to the intensity of the incident wave I i []: where m = ρ / ρ and n = c / c. The attenuation coefficient α s due to the presence of sediments at the sea foor is α s = β f υ where υ is an empirica constant (typicay for many measurements on sands and cays) and β (db/m-khz) depends upon porosity and is approximatey equa to.5. The tota transmission oss is computed as (we refer this case as mode 4) []: I r msin θ ( n cos θ ) TL _ bottom = og og = I i msin θ ( n cos θ ) + ( ) ( ) ( α ) TL = k. og +. og a( f ) +. + TL _ bottom The attenuation corresponding to this oss mode is aso shown in Figure (parameters assumed are: m =.95, n =.86, θ = 5, β =.5, and υ = ). The graph corresponding to mode 5 in Figure considers the combined effect of oss modes -4.. Ambient Noise The ambient noise in ocean is modeed using four sources: turbuence, shipping, waves, and therma noise. Most of the ambient noise sources can be described by Gaussian statistics and a continuous power spectra density (PSD). The foowing empirica formua gives the PSD of the four noise components in db re µ Pa per Hz as a function of frequency in khz []: s (6) (7) 95

og N ( f ) = 7 ( og f ) og N ( f ) = 4 + ( s.5) + 6og f 6 og( f +.) og N og N (8) t s w th ( f ) = 5 + 7.5w / ( f ) = 5 + og f + og f 4 og( f +.4) where w is the wind speed in m/s and s is the shipping activity factor. Figure shows the overa PSD cacuated as N( f ) = N ( f ) + N ( f ) + N ( f ) N ( f ), The PSD decays with frequency..4 Underwater Signa-to-Noise Ratio t s w + Since the transmission oss in a UW channe depends both on frequency as we as the transmission distance, et it be represented by A (, f ). Using A (, f ) and noise PSD N ( f ), the signa to noise ratio (SNR) at the receiver at a distance and frequency f for a transmitted P / A(, f ) power of P and receiver noise bandwidth f is given by γ (. f ) =. Considering N( f ) f absorption and spreading oss aone, the frequency dependent factor in the SNR /[ A (, f ) N ( f )] is potted in Figure for different propagation oss modes. It may be noted that the optimum transmission band depends on ink distance. Further, for each, there exists an optima frequency f ( ) for which maximum SNR is obtained. This is the frequency for which the term / A(, f ) N ( f ) becomes maximum []. The optima frequency is shown in Figure 4 for various oss modes. th. UNDERWATER CHANNEL CAPACITY In this section, we rey on the UW capacity mode given in []. The channe is assumed to be time invariant for some interva of time and the ambient noise is assumed to be Gaussian. Two definitions are used for the capacity: the db acoustic bandwidth and the optima bandwidth.. Capacity Based on db Bandwidth The acoustic db bandwidth B ( ) is the range of frequencies around f ( ) for which γ (. f ) f γ (, f ( )) /. We choose the transmission bandwidth to be equa to B ( ). The transmitted signa power spectra density (PSD) S ( f ) is assumed to be fat over the transmission 96

bandwidth, i.e., S ( f ) = S for f B ( ) and esewhere. The tota transmission power is then P ( ) = S B ( ). The corresponding capacity expression is given as [] P B C = + ( ) / ( ) ( ) og df A f N f B (, ) ( ) ( ) (9) where P ( ) is the minimum transmission power required to ensure that the received SNR is equa to a target vaue γ and is computed as P ( ) = γ B () ( ) B ( ) B ( ) A N( f ) df (, f ) df. Capacity Based on Optima Bandwidth In this section, we consider the computation of capacity based on the notion of an optima bandwidth []. A case in which the transmitted signa PSD S ( f ) is adjusted in accordance with the given channe and noise characteristics was anayzed in []. This adjustment is equivaent to aocating power through water pouring. In the absence of mutipath and channe fading, the optima capacity of a point-to-point ink is given by [] () C( ) = B( ) K og df A(, f ) N( f ) where B () is the optimum band of operation and K is a constant. Here B() is the frequency range over which A(, f ) N( f ) K and ( f ).The corresponding transmitted power is S given by P( ) = S ( f ) df where the signa PSD shoud satisfy the water fiing principe B( ) S ( f ) = K A(, f ) N( f ), f B( ) () The transmission power P () is seected as the minimum power required such that the received SNR equas a target vaue γ and is computed as 97

P( ) = K B( ) A(, f ) N( f ) df B( ) () The optima PSD is then determined through the numerica agorithm in []. 4. NUMERICAL RESULTS The numerica resuts for the capacity and the bandwidth are obtained using MATLAB. The parameters used are wind speed w = m/s, moderate shipping activity s =. 5, and spreading factor k =. 5. The SNR threshod is set to γ db. Figures 5 & 6 respectivey show the = bandwidth and the capacity versus distance based on db bandwidth definition. The resuting bandwidth efficiency is 6.65bps/Hz. Tabe shows the comparison of capacity and bandwidth for different oss modes. It may be noted that both the capacity and the bandwidth decreases drasticay as the transmission distance increases. Assuming absorption and spreading aone, channe capacity is amost equa to 7.kbps for = 4 km whie for the combined oss mode 5, the capacity is.kbps which is equivaent to amost 95% reduction in capacity. For the case of optima bandwidth, the transmitted signa PSD for each distance and for the desired threshod SNR γ is determined using the numerica agorithm mentioned earier. Figures 7 & 8 respectivey show the bandwidth, and the capacity obtained based on the notion of optima bandwidth. The resuting bandwidth efficiency is approximatey equa to 8.5bps/Hz and is isted in Tabe ( = 4 km). The capacity improves by approximatey 78% as compared to that achievabe based on db bandwidth definition. The numerica resuts aso revea that for a the oss modes described in this paper, both bandwidth and capacity decays amost ineary with distance on a ogarithmic scae. 5. CONCLUSION In this paper, numerica resuts for the capacity of time invariant UW point-to-point ink were presented, considering the effects of various acoustic path oss modes and a specific mode of ambient noise PSD. The path oss corresponding to different acoustic propagation phenomena such as surface refection, surface ducts, and bottom bounce, were considered for the capacity cacuation. A comparative assessment of the infuence of these oss modes on the capacity and achievabe bandwidth were presented. 98

6 Attenuation, A(,f) (db) 5 4 mode mode mode mode 4 mode 5 4 6 8 4 6 8 Frequency (khz) Fig.. Attenuation for different propagation oss modes ( ( = km) 5 noise p.s.d (db re micro Pa) 45 4 5 5 5 5 5 frequency (khz) Fig.. Ambient Noise PSD 99

-5 - /A(,f)N(,f) (db) -5 - -5 - mode mode mode mode 4 mode 5-5 4 6 8 4 6 8 Frequency (khz) Fig.. / A (, f ) N ( f ) for different oss modes Optima Frequency (khz) 8 7 6 5 4 mode mode mode mode 4 mode 5 4 5 6 7 8 9 Distance (meters) x 4 Fig. 4. Optima frequency f ( ) vs distance

Bandwidth (khz) mode mode mode mode 4 mode 5-4 5 6 7 8 9 Distance (meters) x 4 Fig. 5. Bandwidth vs distance (db bandwidth definition) Capacity (kbps) mode mode mode mode 4 mode 5 4 5 6 7 8 9 Distance (meters) x 4 Fig. 6. Capacity vs distance (db bandwidth definition)

Bandwidth (khz) mode mode mode mode 4 mode 5-4 5 6 7 8 9 Distance (meters) x 4 Fig. 7. Bandwidth vs distance (optima bandwidth definition) Capacity (kbps) mode mode mode mode 4 mode 5 4 5 6 7 8 9 Distance (meters) x 4 Fig. 8. Capacity vs distance (optima bandwidth definition)

Tabe. Capacity & Bandwidth ( = 4 km) Loss mode Bandwidth( B khz) Capacity( C kbps) Spectra Efficiency Absorption & Spreading Absorption, Spreading & Surface Refection Absorption, Spreading & Bottom Bounce Absorption, Spreading & Surface Duct Combined mode db bandwidth definition Optima bandwidth definition db bandwidth definition Optima bandwidth definition db bandwidth definition ( C / B b/s/hz) Optima bandwidth definition 4. 9. 7.987 75.98 6.658 8.58 4. 9.4 7.987 8. 6.658 8.755.6.75.995.45 6.658 7.5..5.9975.854 6.658 7.656..45.6.78 6.658 8.66 REFERENCES [] I.Akyidiz, D.Pompii and T. Meodia, (5) Underwater acoustic sensor networks: Research chaenges, Esevier Journa on Ad Hoc Networks, vo., issue, pp. 57-79. [] Mari Carmen Domingo, (8) Overview of channe modes for underwater wireess communication Networks, Esevier Journa on Physica Communication, vo., issue, pp. 6-8. [] James Preisig and Miica Stojanovic, (9) Underwater acoustic communication channes: Propagation modes and statistica characterization, IEEE Communications Magazine, vo. 47, no., pp.84-89. [4] M. Stojanovic, (8) Underwater acoustic communications: Design considerations on the physica ayer, proceedings of IEEE/IFIP conference on Wireess On demand Network Systems and Services (WONS 8).

[5] C. E. Shannon, (949) A mathematica Theory of Communication, proceedings of IRE 7, pp. -. [6] M. S. Aouini, and A.J. Godsmith, (999) Capacity of Rayeigh fading channes under different adaptive transmission and diversity-combining techniques, IEEE Transactions on Vehicuar Technoogy, vo. 48, no. 4, pp. 65-8. [7] S. Toumpis and A. Godsmith, () Capacity regions for wireess ad hoc networks, IEEE Transactions on Wireess Communication, vo., pp.76-748. [8] H. M. Kwon and T. Birdsa, (986) Channe capacity in bits per Joue, IEEE Journa on Oceanic Engineering, vo., no., pp.97-99. [9] H. Leinhos, (996) Capacity cacuations for rapidy fading communications channes, IEEE Journa on Oceanic Engineering, vo., no., pp.7-4. [] Donad R. Hummeu, (97) The Capacity of a mode for the underwater acoustic channe, IEEE Transactions on Sonics and Utrasonics, vo. SU-9, no., pp. 5-5. [] Thomas J. Hayward and T. C. Yang, (4) Underwater Acoustic Communication Channe Capacity: A Simuation Study, Proc. of AIP conference, vo. 78, pages 4-4. [] Baakrishnan Srinivasan, (8) Capacity of UW acoustic OFDM Ceuar Networks, MS Thesis, University of Caifornia. [] Miica Stojanovic, (7) On the reationship between capacity and distance in an underwater acoustic communication channe, Proc. of ACM SIGMOBILE MCR, vo., issue 4, pp. 4-4. [4] Miica Stojanovic, (8) Design and capacity anaysis of ceuar type underwater acoustic networks, IEEE Journa of Oceanic Engineering, vo., no., pp. 7-8. [5] Miica Stoja novic, (7) Frequency reuse underwater: capacity of an acoustic ceuar network, proceedings of second ACM Internationa Workshop on Underwater Networks, 7. 4