T. S. Rappaport, Wireless Communications. Upper Saddle River, New Jersey: Prentice Hall, 1999.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....denoted as i=j I 1j (t) consisting of both intercell interference and intracell interference, is a key parameter limiting the capacity of CDMA systems. We note that the intracell interference I 11 can be eliminated by using orthogonal spreading in downlink if multipath does not exist [9] [16]. The above model has its root in the earlier work [12] One key difference between our study and theirs is that [12] presented a snapshot analysis for some power control algorithms for the uplink, whereas we take into account the burstiness of the ON OFF users, and characterize interference and ....

....MAI structure at coarser time scales to explore admission control for data applications. For systems with voice users, admission control is based on the network capacity, which is defined as the maximum number of users that can be supported without violating their average SINR requirements [16], 17] This approach, however, cannot be applied directly to systems with data users because of the highly bursty MAI (and hence SINR) even at large time scales. We expect that admission control schemes using the mean value of the SINR (or equivalently MAI) over one session would not work ....

T. S. Rappaport, Wireless Communications: Principles and Practice. New Jersey: Prentice Hall, 1996.

....that it could potentially utilize. This is a dicult problem, since the e ective latency and bandwidth betw een a mobile host and other nodes is constantly changing. This may be due to ad hoc topology changes, vertical hando across connection alternatives, or wireless fading and shadowing [14, 23]. These causes are in addition to the more prosaic routing changes and congestion endemic to wired networksofeven modest scale [16, 22] T ogether, these factors conspire to produce frequentchanges in a vailable latency and bandwidth, and induce substantial noise in individual netw ork ....

T. S. Rappaport. ######## ######################### ### ########. Upper Saddle River, New Jersey:Prentice Hall, 1996.

....### I ### #t#. The MAI, consisting of both intercell interference and intracell interference, is a key parameter limiting the capacity of CDMA systems. We note that the intracell interference I ### can be eliminated by using orthogonal spreading in downlink if multipath does not exist [9] [15]. 0 7803 7476 2 02 17.00 (c) 2002 IEEE. The above model has its root in the earlier work [11] One key difference between our study and theirs is that [11] presented a snapshot analysis for some power control algorithms for the uplink, whereas we take into account the burstiness of the ON OFF ....

....the MAI structure at coarser time scales to explore admission control for data applications. For systems with voice users, admission control is based on the network capacity, which is defined as the maximum number of users that can be supported without violating their average SINR requirements [15], 16] This approach, however, cannot be applied directly to systems with data users because of the highly bursty MAI (and hence SINR) even at large time scales. We expect that admission control schemes using the mean value of the SINR (or equivalently MAI) over one session would not work well. ....

T. S. Rappaport, Wireless Communications: Principles and Practice. New Jersey: Prentice Hall, 1996.

....as R i = 2 i 10 i =10 Ar i P T where the transmitted power, P T , and the deterministic propagation parameters, A and , are taken to be constant and equal for all users in the system. We shall assume the typical value of = 4 as is generally the case in urban cellular systems [5][12]. B. Capture Model The capture model we consider in this paper is a threshold model based on the signal to interference ratio (SIR) at the receiver [2] 5] When SIR is greater than a predetermined threshold, T , one packet (out of all the colliding packets) is correctly received with probability ....

T. S. Rappaport, Wireless Communications: Principles and Practice, Upper Saddle River, New Jersey: Prentice-Hall, 1996.

....approximately as Gaussian. More accurate distributional models exist [15] but we believe that the Gaussian approximation adequately serves our goals in this work. VIII. APPENDIX Below is the sketch of the proof of the asymptotic variance of m K . The proof closely follows Appendix C in [19]. After downconversion to the baseband, despreading and integration over one chip duration, m k = r P k 2 cos k fX k k Y k (T c k )g where X k and Y k denote respectively the product of c i 0 with c j k and c j 1 k , for some i; j, due to the lack of synchronization. The ....

T. S. Rappaport, Wireless Communications: Principles and Practice, Upper Saddle River, New Jersey: Prentice-Hall, 1996.

....a mobile host and other nodes is constantly changing. This may be due to ad hoc topology To appear in the Proceedings of the ACM Conference on Mobile Computing and Networking, Rome, Italy, June 2001. changes, vertical handoff across connection alternatives, or wireless fading and shadowing [14, 23]. These causes are in addition to the more prosaic routing changes and congestion endemic to wired networks of even modest scale [16, 22] Together, these factors conspire to produce frequent changes in available latency and bandwidth, and induce substantial noise in individual network ....

T. S. Rappaport. Wireless Communications:Principles and Practice. Upper Saddle River, New Jersey:Prentice Hall, 1996.

....amount of energy one can devote to processing power and wireless transmission. 2 Wireless networks also give rise to substantial challenges. Wide area coverage necessarily provides lower bit rates to individual devices [17] using channels that exhibit rapidly, dramatically changing performance [22]. The frequency of change depends on the speed of the mobile device. Slow moving users may have bad signal quality for long periods, and fast moving users may suffer from channels that are difficult to measure and react to. Our target application presents its own difficulties. Interactive video ....

....only when the channel is actually poor. In this section, we present the performance of three control schemes: no adaptation, power adaptation, and power combined with rate adaptation. These schemes are evaluated using a simulation of the wireless link. We simulate a Rayleigh fading distribution [22] using Clarke s model [6] it assumes that multiple reflected waves will arrive with arbitrary phase and angle of arrival. Shadowing is simulated directly from an autocorrelation of the process, which has been shown to give results closely matching physical channels [11] Our Rayleigh fading ....

T. S. Rappaport. Wireless Communications:Principles and Practice. Upper Saddle River, New Jersey:Prentice Hall, 1996.

....to provide the best possible service. Unfortunately, providing such estimates is difficult at best. Network observations are noisy, particularly over widearea [1] or mobile [2] paths. Such networks also suffer from persistent changes in performance due to vertical handoff [3] wireless fading [4], or routing changes [5] Good network estimators should ignore transient noise conditions, but react quickly to persistent changes in performance. We call the former property stability, and the latter agility. Typically, network estimators in the form of exponentially weighted moving average ....

T. S. Rappaport, Wireless Communications:Principles and Practice, Upper Saddle River, New Jersey:Prentice Hall, 1996.

....bit error probability over the conventional linear receiver in impulsive channel. When noise is Gaussian, the robust procedure su ers a marginal performance deterioration. VII. Appendix Below is the sketch of the proof of the asymptotic variance of m K . The proof closely follows Appendix C in [6]. After downconversion to the baseband, despreading and integration over one chip duration, m k = r Pk 2 cos kfXk k Yk (Tc k )g where Xk and Yk denote respectively the product of c i 0 with c j k and c j 1 k , for some i; j, due to the lack of synchronization. The former overlap is ....

....Robust, Impulsive Ch. Linear, Impulsive Ch. Sim. Robust, Impulsive Ch. Sim. Figure 5 Bit error probability of the robust single user receiver and the matched lter against the number of active users (R b = 9600 bps, E b =N0 = 5 dB, 0:2, 20, N = 31) and assuming uncorrelated interferers [6] varf m K jf kg; f kg; fPkgg = K 1 X k=1 E[ m k ) 2 jf kg; f kg; fPkg] K 1 X k=1 T 2 c Pk 2 cos 2 kE[W 2 k jf kg; f kg; fPkg] where Wk = Xk k Yk (Tc k ) and Xk and Yk are uncorrelated. E[W 2 k jf kg; f kg; fPkg] Pk 2 cos 2 kfT 2 c 2Tc k 2 2 k g: ....

T. S. Rappaport, Wireless Communications: Principles and Practice, Upper Saddle River, New Jersey: Prentice-Hall, 1996.

....power and refer to it as the 1 d 4 field. In the 1 d 2 field the gain is proportional to 1 d 2 ; however, we concentrate on the field since this is where the greatest degree of spatial reuse is exploited. The gain in the 1 d 4 field is sometimes modeled as the 2 ray ground reflection model [13, 14, 15] G ij = A d # ij , 1) where A is a constant that accounts for the signal strength gains from the transmitter and receiver antennas and their heights, d ij is the distance between nodes i and j, and # is the path loss exponent (where # = 4 is the value typical chosen) This is also the model ....

.... (where # = 4 is the value typical chosen) This is also the model used for the CMU mobile extensions to the ns2 simulator [16] While this model is appropriate for flat and open areas, objects in the path between a transmitter and receiver may introduce additional interference such as shadowing [13, 14, 15], which results in a log normal contribution to the gain to produce a slow fading model G ij = A d # ij 10 # 10 , 2) which is referred to as log normal shadowing. In addition to shadowing, the signals may follow multiple paths (each with independent shadowing) from the transmitter to ....

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T. Rappaport, Wireless Communications: Principles and Practice. New Jersey: Prentice Hall, 1996.

....aaz rice.edu. 1 is due to the channel dynamics produced by the multiple mobile scatterers encountered in transmission. Multiaccess interference, on the other hand, is caused by the multiple users simultaneously using the channel. The RAKE receiver structure is used in practice to combat fading [1, 2], and various multiuser detection schemes have been proposed [3] to overcome multiaccess interference. Recently, multiuser RAKE receivers have been proposed to combat multiaccess interference in fading channels [4, 5] However, such schemes are applicable only in slow fading scenarios in which the ....

....diversity by attaining larger values of TB d [9, 10, 11, 17] more discussion in Section 3.3) 2. 2 Multiuser Signal Model For a CDMA system with K users and employing synchronous coherent BPSK signaling, such as may be encountered in the downlink of a mobile communication system [2, 18], the signal at the input of the receiver is given by r(t) x(t) n(t) I X i= GammaI K X k=1 b k (i)x i k (t) n(t) 10) 3 The approximation in (5) can be made arbitrarily close by including more summation terms. However, most of the energy is captured by the (L 1) 2M 1) terms ....

T. S. Rappaport, Wireless Communications. New Jersey: Prentice Hall, 1996.

....and ECS 9979448. 1 Permission to publish this abstract separately is granted. 0 1 Introduction Mobile wireless channels are characterized by time varying multipath propagation effects and accurate estimation of time varying channel parameters is critical to reliable coherent communication [1, 2]. Indeed, emerging wireless standards accommodate pilot signal transmissions dedicated for channel estimation [3, 4] In this paper, we address time varying channel estimation for spread spectrum code division multiple access (CDMA) systems that have emerged as a promising core wireless ....

....errors on coherent receiver performance. Channel estimation in mobile scenarios depends on the time scale of variation in channel parameters. For coherent estimation, a key channel characteristic is the coherence time, Deltat c , over which the channel coefficients remain strongly correlated [1, 2]. The coherence time is inversely proportional to the Doppler spread encountered during propagation. Essentially, Deltat c limits the duration over which time averaging can be done to improve channel estimation. This paper focuses primarily on single user systems. We develop a framework for ....

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T. S. Rappaport, Wireless Communications. New Jersey: Prentice Hall, 1996.

....components depends on the spectral signaling resolution (1=T ) P = dTBde. The total number (L 1) 2P 1) of components is thus proportional to the product TmBd and the signaling time bandwidth product (TBP) TB, and is typically small due to the underspread (TmBd 1) nature of practical channels [8, 7]. L P MULTIPATH DOPPLER q t T c T 1 Figure 1. Sampling of the time frequency plane inherent in the canonical channel representation. In the WSSUS model, H( is modeled as a family of uncorrelated Gaussian random variables characterized by [5] 1 Psi( E[jH( j 2 ] The ....

T. S. Rappaport, Wireless Communications. New Jersey: Prentice Hall, 1996.

....direction for future research is the use of block processing to achieve Doppler diversity via some form of sequence decoding. Such a scheme could be applicable in existing systems such as the IS 95 standard in which a block of 200 symbols is processed together for the purpose of interleaving [28]. In addition to novel signaling and receiver structures, the canonical time frequency channel representation can be leveraged in several other aspects of system design. In particular, in Section 6 we developed a framework for multiuser timing acquisition based on quadratic processing. The ....

T. S. Rappaport, Wireless Communications. New Jersey: Prentice Hall, 1996.

....conventional RAKE receiver. The conventional RAKE receiver is adequate only for slow fading situations in which the channel characteristics vary slowly over time. However, in many mobile communication scenarios, temporal channel variations often become significant and must be taken into account [2]. For example, such rapid channel variations are encountered in intersatellite and underwater acoustic communication systems [3, 4, 5] Multicarrier CDMA systems involve lower data rates in which intrasymbol channel variations can become significant (see, for example, 6] Similarly, the ....

....in [7] suggest spreading codes that are much longer than the intersymbol period, thereby necessitating significant channel variations within the effective symbol period. The RAKE receiver is suboptimal in such fast fading situations and can suffer from substantial degradation in performance [2]. Noncoherent RAKE receiver is often used in practice, at the expense of a 3dB loss in performance, to provide robustness to the Doppler shifts induced by the temporal channel variations. The new framework proposed in this paper effectively exploits rapid channel variations for improved ....

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T. S. Rappaport, Wireless Communications. New Jersey: Prentice Hall, 1996.

....are no temporal channel variations within a symbol period, and is thus adequate only for slow fading situations in which the channel characteristics vary slowly over time. In many mobile communication scenarios, temporal channel variations often become significant and must be taken into account [2]. For example, such rapid channel variations are encountered in intersatellite and underwater acoustic communications systems [3, 4] Multicarrier CDMA systems involve lower data rates in which intrasymbol channel variations can become significant (see, for example, 5] Similarly, the techniques ....

....thereby necessitating significant channel variations within This work was supportedby the National Science Foundation and the Texas Advanced Technology Program. the effective symbol period. The RAKE receiver, which ignores temporal variations, is suboptimal in such fast fading situations [2] and can suffer from substantial degradation in performance. Noncoherent RAKE receiver is often used in practice, at the expense of a 3dB loss in performance, to provide robustness to the Doppler shifts induced by the temporal channel variations. In this paper, we propose a new framework that ....

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T. S. Rappaport, Wireless Communications. New Jersey: Prentice Hall, 1996.

.... receiver is optimal under, and provides a substantial guard against, slow fading in which the channel characteristics vary slowly over time [1] However, the increased mobility of users in cellular communications often results in fast fading in which the channel exhibits rapid temporal variations [2, 1, 3]. The resulting Doppler spread induced in the signal substantially degrades the performance of the RAKE receiver due to errors in channel state estimation [3, 4, 5, 6] In fact, existing systems exhibit a limiting bit error probability (BEP) floor under such conditions that cannot be improved by ....

....[1] The basic idea is to transmit the signal over (L 1) independent fading channels, while keeping the total power constant by transmitting at a lower power in each channel. Common diversity techniques include antenna diversity, time diversity, frequency diversity and polarization diversity [1, 2, 3]. The dashed curves in Figure 2 illustrate the performance improvement due to coherent diversity processing [1] It is evident that performance improves monotonically with increasing L. In fact, as L 1, the performance of coherent diversity reception converges to the performance over a nonfading ....

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T. S. Rappaport, Wireless Communications. New Jersey: Prentice Hall, 1996.

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T. S. Rappaport, Wireless Communications. Upper Saddle River, New Jersey: Prentice Hall, 1999.

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T.S. Rappaport, Wireless Communications Principles and Practice, New Jersey: Prentice Hall, 1999.

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Rappaport, T. S., Wireless Communications: Principles and Practice, New Jersey: Prentice Hall, 2002, pp. 7.

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T. S. Rappaport, Wireless Communications --- Principles and Practice, New Jersey: Prentice Hall, 1996.

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T. S. Rappaport, Wireless Communications: Principles and Practice. Upper Saddle River, New Jersey: Prentice-Hall, Inc., 1996.

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Rappaport, T. S., Wireless Communications, New Jersey: Prentice-Hall,

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T. S. Rappaport, Wireless Communications. Upper Saddle River, New Jersey: Prentice Hall, 1999.

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T. S. Rappaport. Wireless Communications:Principles and Practice. Upper Saddle River, New Jersey:Prentice Hall, 1996.

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