On the Radio Capacity of TDMA and CDMA for Broadband Wireless Packet Communications

On the Radio Capacity of TDMA and CDMA for Broadband Wireless Packet Communications Srikanth V.Krishnamurthy,Member,IEEE,Anthony S.Acampora,Fellow,IEEE,

and Michele Zorzi,Senior Member,IEEE

A BSTRACT

Studies of the capacity of cellular systems,stated in terms of the admissible number of remote users,have generally been lim-ited to voice telephony.In this paper,we address the problem of comparing the interference-limited performance of CDMA and TDMA systems in a packet switched environment.The objec-tive is to determine whether the capacity advantages claimed for circuit-switched CDMA still apply in a packet-switched envi-ronment,where the natural time diversity of bursty transmission may be a signi?cant factor.Under a set of speci?c assumptions about the wireless environment(including path loss,shadow fading,multipath delay spread,co-channel interference,power control,coding),we evaluate the number of users which can be admitted to the system while maintaining some desired Quality-of-Service level.Four different classes of users with different characteristics and requirements are considered.The system ca-pacity is found to signi?cantly depend on the QoS objectives, which might be stated in terms of availability of some speci?ed signal to interference level,packet loss rate,or mean tolerable delay.The main?nding is that strict requirements imposed on the radio access level tend to favor CDMA,whereas if some form of packet recovery at the higher layers is allowed(imply-ing a relaxed set of requirements on the radio interface),then a somewhat higher capacity may be achieved by TDMA.

I I NTRODUCTION

Within the?eld of modern telecommunications,there has re-cently emerged a strong interest in supporting portable devices capable of wireless communications.Accordingly,Wireless ATM, wherein the concept of bandwidth upon demand is carried over to the wireless world[1]-[2],has enjoyed increasing attention. Seamless extension of ATM from the high bandwidth and low error rate wireline network to the low bandwidth and high error rate wireless network introduces a series of interesting and chal-lenging issues.The harsh fading nature of the wireless chan-nel,and interference due to simultaneous use of the bandwidth by multiple users,cause conditions wherein the intended signal may not be received with satisfactory quality at the base sta-tion.While power control may be a partial solution for combat-ing signal loss due to propagation effects,it is also necessary to limit the number of users simultaneously admitted into a system consisting of a cluster of cells in order to keep the interference S.V.Krishnamurthy is with the Department of Computer Science and Engineering,Uni-versity of California,Riverside,CA,92521,e-mail:krish@https://www.wendangku.net/doc/9e10257801.html,;A.S.Acampora is with the Department of Electrical and Computer Engineering,University of California,San Diego,La Jolla,CA,92093,e-mail:acampora@https://www.wendangku.net/doc/9e10257801.html,;M.Zorzi is with the Dipar-timento di Ingegneria,Universit`a di Ferrara,Italy,e-mail:zorzi@ing.unife.it.at acceptable levels and to enable hand-off of live connections without unacceptable rates of cell overload or call dropping. The goal of a call admission control policy is to admit to the system as many users as possible while maintaining the Quality-of-Service(QoS)guarantees of ongoing and incoming calls[3]. The system capacity is then de?ned as the total number of users that can be admitted to the system.Following a common prac-tice in the literature,we will express this capacity in terms of users per cell,although this number is to be interpreted as an average value since,once a user is admitted to the system,it can roam throughout the service area,and the actual number of users in each cell is a random variable.

Studies of cellular system capacity have been reported in the literature,but most of these have been limited to circuit switched narrow band voice communications[4]-[6].In[4],the CDMA (Code Division Multiple Access)scheme was compared to static TDMA/FDMA(Time Division Multiple Access/Frequency Di-vision Multiple Access)schemes,and the authors showed that, for telephone traf?c,the capability of the CDMA system to tol-erate high levels of adjacent cell interference helps in achieving a substantial capacity gain with respect to?xed channel alloca-tion TDMA/FDMA schemes.

This paper complements these studies by considering a wire-less network serving constant-bit-rate(CBR)or variable-bit-rate (VBR)users in a packet switched environment.The objective is to estimate and compare the capacity of packet TDMA and packet CDMA approaches.As a?rst step towards this goal,in this paper we restrict ourselves to a wireless network carrying a single,homogeneous traf?c class(i.e.,all remotes generate the same type of traf?c),and several such single traf?c classes are considered.Possible extensions to compute the capacity regions when the network carries multiple traf?c classes with different traf?c characteristics and QoS requirements can be envisioned but are beyond the scope of this paper.

In an attempt to be thorough,we explicitly account for path loss,shadowing,multipath delay spread and co-channel interfer-ence.Further,we investigate the effects of error control coding and power control.We consider convolutional codes of differ-ent rates to quantify the effects of error control coding.Two types of power control are considered:(a)coarse power control wherein the power control mechanism compensates only for the pathloss and the shadowing experienced by a user,and(b)?ne power control wherein the mechanism is such that it compen-sates for multipath fading as well.Note that in the latter case the received signal strength due to any remote user’s transmis-sion at the base station is constant.Depending on the type of traf?c class considered and on the constraints imposed,different

QoS metrics may be de?ned.Most of the QoS metrics consid-ered in this work depend on the signal to interference ratio(SIR) at the receiver being greater than a threshold value,?xed a pri-ori.Since closed form expressions for the SIR are dif?cult to obtain,we use a combination of simulation and analytical mod-els to estimate the statistics of the SIR under various conditions. In this paper,we are concerned with the radio access per-formance,i.e.,we do not consider higher-layer techniques to recover from transmission errors.In order to draw more de?ni-tive conclusions,one must couple such a study with the anal-ysis of protocols at the data-link layer and above.The results we present in this paper provide insight which can lead to for-mulating meaningful simpli?ed models for the study of these higher-layer issues.

A somewhat general conclusion which can be drawn from our results is that protocols or applications requiring very stringent access performance(e.g.,in terms of packet loss rate)would bene?t from higher protection as provided by CDMA,whereas protocols and applications which can work in the presence of relatively high packet error rates(e.g.,through ef?cient retrans-mission error recovery)can accommodate a larger number of users if TDMA mode is chosen.In the environment under con-sideration,we are able to characterize this trade-off and to iden-tify the CDMA and TDMA cross-over point.

We limit ourselves to the study of the performance of the re-verse link(i.e.,remote-to-base transmission link).Due to the multiple access nature of the reverse link,one might expect that the forward link performance would be at least as good as that of the reverse link[8].Ignored throughout are such practical mat-ters as synchronization since we are exclusively interested in comparing the capacities of the two systems as fundamentally limited by propagation effects and multiple access interference. In Section2,we present our system model,including prop-agation effects and allocation strategies used for CDMA and TDMA.Also described in Section2are the different classes of traf?c considered and the simulation and analytical models.A discussion of the results is presented in Section3.

II S YSTEM A SSUMPTIONS

A Model of the physical layer

The wireless network is assumed to be divided into regions consisting of contiguous radio cells.Each cell contains a cen-trally located base-station,and the base stations are deployed in a hexagonal arrangement.For traditional TDMA cellular sys-tems,a seven-cell reuse pattern is often deployed[9].This re-sults in a6/7capacity penalty,which may not be needed in sys-tems where the?exibility of packet switching can be exploited. Therefore,in our work,we assume that the entire bandwidth is reused in every cell for both TDMA and CDMA systems. This may be pessimistic in a TDMA setting,where some in-terference protection(e.g.,via dynamic channel allocation)can help the performance.However,due to the already considerable complexity of the present study,we leave consideration of such schemes for further work.

The propagation model considered throughout accounts for a number of effects.Path loss and shadowing are modeled as the inverse fourth power of the distance,,and a log-normal random variable,,respectively,so that the signal power re-

ceived from a user,averaged over multipath,is proportional to .Based on this quantity,users are assigned to the best

base station,i.e.,the one with smallest long-term attenuation.

This assignment strategy guarantees signi?cantly improved per-formance with respect to the case of closest base station as-

signment[10,11].The effect of multipath fading[12]-[14]is modeled by means of a complex Gaussian impulse response,

,with exponential multipath intensity

pro?le,i.e.,if and0otherwise. The quantity is the delay spread of the channel.As to the second-order statistics of the channel,we consider here for sim-

plicity the block-fading channel model,in which the channel impulse response does not change within a slot,but is indepen-dently chosen slot-by-slot.This model also accounts for the ef-fects of user mobility(not explicitly modeled in our MonteCarlo simulations),assumed here suf?cient to make successive trans-missions experience independent fading conditions.Notice that this assumption of fading independence would also correspond to the use of frequency hopping techniques.

For every packet transmission,we compute,at the receiver, the Signal-to-Interference Ratio(SIR),and assume that the packet is correctly received if and only if the SIR is above a preset threshold,which depends on the details of the physical layer. In particular,the receiver is assumed to consist of a perfectly coherent?lter matched to the waveshape produced when a rect-angular transmit pulse is“?ltered”by the impulse response of the multipath channel.In addition,in the TDMA system,we assume the presence of a zero forcing equalizer which negates the intersymbol interference(ISI)caused by the delay spread of the channel.For both CDMA and TDMA,QPSK modulation is assumed.In order to focus on the interference-limited nature of the systems,thermal noise is neglected throughout.

For a fair comparison,the channel data rate is assumed to be the same for both CDMA and TDMA.In CDMA,the channel data rate is actually the chip rate,with the actual user informa-tion rate being times slower,where is the spreading gain of the CDMA modulation.On the other hand,in TDMA,a user transmits at peak channel rate only during a fraction of the time, resulting again in an actual information rate equal to times the peak channel rate.More speci?cally,we assume a slotted time axis(see Figure1).Each slot accommodates exactly one TDMA packet.A frame structure is superimposed,where a frame consists of slots.Note that,because of the bandwidth spreading,a CDMA packet will occupy an entire frame(i.e., slots).

B Traf?c models

In this paper,we separately and independently consider four

traf?c classes,representative of a variety of possible services. Type1:CBR Traf?c.The?rst class considered is CBR traf-

Note that for CDMA this corresponds to an ideal RAKE receiver with an in?nite num-ber of?ngers.

Note that,strictly speaking,this is true only when no coding is used.If the information sequence is coded before transmission,the effective CDMA spreading gain seen by the encoded stream is reduced according to the code rate,since is the ratio between channel rate and user information rate.

In this case as well,if coding is used the slot occupancy of a TDMA packet is increased according to the code rate,so that both information rate and channel symbol rate are kept ?xed.Speci?c explanation is given in Section2.4.

?c,which may,for example,represent real-time voice or video.

For the entire duration of the call,each active CBR user gen-erates packets periodically,at the rate of one packet per frame.

Each user is then assigned the same slot in every frame,much

like in a circuit-switched system.In this case,interference can be assumed to be persistent(since the same group of users will

likely interfere for an extended period of time),and therefore we choose as the QoS metric the probability of outage,i.e.,

the marginal probability that the SIR is below threshold(in this

case,we can assume that the connection will be unacceptably degraded and will therefore be dropped).In the case of speech

transmission,packet switching allows discontinuous speech ac-

tivity to be exploited,through the Speech Activity Detection (SAD)mechanism.In this case,users generate packets only

for some fraction of the time(taken to be about40%in the numerical results)[4].In CDMA,this results in a proportion-

ally decreased interference,whereas in TDMA this allows the

bandwidth manager to dynamically reallocate slots among ac-tive users.

Unlike class1,traf?c classes2,3and4consist of bursty

packet traf?c(VBR).In CDMA,whenever a user sends a packet, the channel is occupied for the entire frame duration,and several

overlapping packets may be transmitted in the same frame.In TDMA,a perfect media access protocol is assumed,and the sys-

tem is able to schedule transmissions so that users in the same

cell will transmit in different slots within a frame.Coordina-tion among different cells,though a possibility,is not considered

here.

Type2:Packet Traf?c with no retransmissions allowed.Traf-?c class2is a limiting case,with no provision for queueing re-mote users’packets.Each remote user generates a packet in a frame with probability,and that packet is transmitted in the subsequent frame.As before,transmissions for which the SIR is below threshold are unsuccessful,and no retransmission is allowed.Unlike CBR traf?c,consecutive randomly generated VBR Class2packets encounter different interference power lev-els since the number of access attempts per slot(TDMA)or frame(CDMA)and the set of interfering users are random.Due to this time diversity feature of packet switching,the fact that the SIR is not adequate during a single packet transmission does not mean that the whole connection will experience poor qual-ity.An appropriate QoS measure for this traf?c class is then the probability that the instantaneous packet loss rate exceeds some predetermined value.

Type3:Packet Traf?c with retransmissions allowed and no delay constraints.In traf?c class3,a remote user’s queue is assumed to always contain packets awaiting transmission and a user transmits a packet in a frame with probability.If a transmission attempt is unsuccessful,the failed packet is sched-uled for retransmission after some random delay.No constraint is imposed on the value of this delay,nor on the number of transmission attempts allowed for a given packet.The remote queue is assumed to be of in?nite size,so that,eventually,all packets are successfully delivered if the system is stable.Note We assume here the availability of a perfect bandwidth assignment mechanism,so that the potential of SAD in TDMA can be fully exploited.

Note that this is not possible if the number of active users in a frame exceeds the number of slots.However,in all cases of interest,this event has negligible probability and will be ignored.that different transmission attempts are subject to different fad-ing/interference effects by virtue of time-diversity.Let the steady-

state probability of successful transmission,when,there are(on average)users per cell,each transmitting with probability, be denoted by.The probability that a user success-

fully transmits in a slot(service rate)is given by

,and,for this case,the maximum value,

is the performance metric.The maximum achievable collective throughput per cell(saturation throughput)is then given by

is then given by[15]

(2) In order to minimize the mean delay,for a given input rate of ,the average service rate must be maximized with respect to,taking into account that and

that the probability that a given remote user’s queue is empty is given by

(4)

In the above equation is the interference experienced by the packet due to simultaneously transmitting interferers and a self noise component(due to frequency selective fading) and is given by:

(5)

where and

.

In Appendix B,we show that under the same conditions,the SIR for TDMA is

ical/simulation technique described in the previous section,are presented in terms of QoS metric(which is different for differ-ent traf?c classes)vs.the average number of admitted users per cell.As a general conclusion,we observed that the capac-ity assessment of TDMA and CDMA signi?cantly depends on the QoS metrics chosen and on the QoS requirements.Typi-cally,CDMA better satis?es strict QoS constraints(i.e.,small packet error rates),due to its inherent ability to tolerate some degree of interference while still providing good quality.On the other hand,TDMA is more sensitive to moderate or high levels of interference,and therefore in this context it offers a higher capacity when less stringent requirements are placed on the physical/access layer.It should be noted that this does not mean that TDMA cannot be used for high-quality communica-tions,since time diversity coupled with the short durtion of the TDMA packets allows for the recovery at higher layers(e.g., data-link)of those packets which are lost on the radio interface. The study of these higher-layer protocols is,however,beyond the scope of the present paper,but our results may be applicable to such a future study.

In the simulations,we assume that satisfactory signal quality can be achieved with a SIR of8dB(computed after the front-end processing,including despreading,decoding and equaliza-tion as applicable).The standard deviation of the lognormal shadowing is assumed to be8dB.To fully capture interference effects,the geographical region under consideration is a cluster of61cells.The use of error-control codes is assumed to yield asymptotic coding gains.In particular,for convolutional codes with soft decision decoding,the coding gains assumed are7dB for a rate1/2code,7.3dB for a rate1/3code,and7.4dB for a rate1/4code,respectively[16].If hard decision decoding is used,the coding gain is about3dB smaller.The constraint length for each of these codes is7.We also considered a rate 2/3code with a constraint length of4for equivalent decoder complexity.For this code,the asymptotic coding gain is5.2 dB with soft decision decoding.Finally,before we discuss our results we list again,some of the primary assumptions that we make.

We assume a frequency reuse factor of one for both CDMA and TDMA systems.

We assume two types of power control.Coarse power con-trol compensates for pathloss and shadowing.Fine power control compensates for multipath fading as well.

We assume that a zero forcing equalizer is used with the TDMA system and that this equalizer completely elimi-nates time dispersion for the desired signal.

In TDMA,a perfect medium access control protocol is present.This protocol allows transmissions to be sched-uled such that users within a cell transmit in different time-slots within a frame.

We ignore synchronization issues

We note that some of these assumptions affect the numerical results presented,and such effects may be different for TDMA and CDMA.On the one hand,note that some assumptions fa-vor CDMA(e.g.,perfect synchronization)while others favor TDMA(e.g.,perfect MAC).On the other hand,the main?nd-These assumptions were described earlier in Section2.ings of this study,e.g.,the fact that the relative performance of CDMA and TDMA depend on the QoS speci?cations and on

the type of traf?c,is still qualitatively true.Therefore,although a more precise assessment of this comparison should take into account more details,what is presented here is a valuable?rst

step towards a fuller understanding of the issues involved.

A Results for CBR traf?c

We present?rst some results for the Type1traf?c,i.e.,CBR

traf?c.Figure2illustrates the effects of power control on both TDMA and CDMA,for and(unless other-wise noted,these parameters will be used for all results in the

following).It can be clearly seen that,as expected,CDMA ben-e?ts from the use of?ne power control,compared to the case of coarse power control(performance with no form of power con-trol is not considered for CDMA).On the other hand,TDMA shows a very robust behavior with respect to the type of power control used,with essentially the same performance in both cases, which in turn is signi?cantly better than no power control at all. This can be explained by the fact that TDMA packet successes mostly occur when there is almost no interference,in which case the performance depends more on proper equalization than on the intended signal power.We also studied the effect of chang-ing the value of(not shown in the Figure):as expected, by doubling,one can approximately admit twice as many users,so that results for higher values of can be similarly extrapolated.Note,however,that increasing requires that either the information rate be decreased or the bandwidth be in-creased.Also,consistent with[4,7],the results shown in Figure 3con?rm that the use of SAD produces approximately a capac-ity2.5times larger(for a speech activity factor of40%). Figure4illustrates the effects of using convolutional codes of different rates in a CDMA system.No SAD is considered here, but a good approximation for the case with SAD can be derived by appropriately scaling the results shown.It is seen that choos-ing a code rate smaller than1/2does not result in any further sig-ni?cant improvement,due to similar values of the coding gain. In the rest of the paper,a rate1/2code will therefore be used.

In Figure5(also with no SAD),we present a direct compar-ison between TDMA and CDMA for the CBR traf?c class for some speci?c conditions.The curves can be seen to cross at some critical value of the outage probability(e.g.,about0.02 when a rate1/2code is used).CDMA allows more users to be admitted than TDMA when the constraint on the outage proba-bility is smaller than this critical value,whereas if outage prob-abilities larger than the critical value are permitted,TDMA pro-vides higher capacity.The CDMA system can easily enjoy the bene?ts of SAD,so that the capacity results as given in Figure 5can be multiplied by a factor of2.5.For an outage probability of less than0.01,results indicate that about users may be admitted to the CDMA system.The performance ben-e?t provided by SAD and cell sectorization cannot be as easily achieved in circuit-mode TDMA.However,if one is willing to accept the additional complexity of dynamic slot reassignment, Note that this may not be true for smaller values of,where the behavior is not linear.

Note that,as the code rate is decreased,the coherence gain due to the fact that coded symbols combine coherently while noise combines incoherently is counterbalanced by the corresponding loss in processing gain seen by the coded sequence.

the same capacity gains can be achieved for both TDMA and CDMA.

The fact that the curves for CDMA and TDMA cross at some point is an important result,and being able to quantitatively identify that critical point and to study its sensitivity to the var-ious environmental factors may be key for ef?cient design of the access scheme.For example,we found that the crossing point moves to the right(i.e.,the regime over which CDMA provides higher capacity increases)if the frequency selectivity of the channel increases.In fact,the performance of the CDMA scheme improves with an increase in delay spread,since this translates into greater received signal power because there are then more resolvable paths(recall that we assume here a per-fectly matched?lter at the receiver,which can resolve all paths). On the other hand,the performance of TDMA is relatively in-sensitive to the value of,since the effect of the delay spread in this case(i.e.,the ISI)is removed by the equalizer.

B Results for VBR traf?c

In this subsection,we present results for the three VBR classes as described in Section2.

The QoS measure considered for Traf?c Class2(VBR traf-?c with no queueing permitted at the remote)is the probabil-ity that the packet loss rate exceeds some maximum tolerable value.The packet loss rate suffered by any user is dependent on the interference experienced by that user.The interference in turn depends on the propagation conditions of all simultane-ously transmitting users.In Figure6,we have considered two values for the maximum tolerable packet loss rate,i.e.,1%and 10%.We remark once again that the packet loss considered here is observed at the radio access level and,while certainly affect-ing the performance of protocols and applications at higher lay-ers,it is not representative of the quality perceived by the user. In other words,this study is mostly concerned with lower-layer performance,whereas a higher-layer study based on the results here presented still needs to be addressed in order to fully char-acterize the QoS enjoyed by the applications.

The sensitivity of the CDMA system to the value of the tol-erated packet loss rate is relatively small due to the fact that spread spectrum provides good protection against moderate in-terference.For typical values of SIR,stricter requirements of no more than1%packet loss are usually satis?ed,whereas under heavy interference conditions,CDMA breaks down and can-not meet even looser loss requirements of10%.On the other hand,the outage probability for TDMA is very dependent on the threshold packet loss objective;for our range of parameters, a10%objective can be met whereas a1%objective cannot. Figure6shows the probability of outage,i.e.,the probability that the instantaneous packet loss probability exceeds a speci-?ed value,denoted by in the graph labels.Consistent with the above discussion,Figure6shows that,if the packet loss rate must be1%or lower,CDMA in general provides higher capac-ity(if we want a packet loss rate of no more than1%at least 90%of the time,when a rate1/2code is used,CDMA provides For very large values of the delay spread,the performance of TDMA will be affected by interference enhancement in the equalizer,leading to degraded SIR.

The value of the outage probability may be interpreted as the long-term average of the fraction of time a user experiences a packet loss rate in excess of,or equivalently the fraction of users experiencing the same condition throughout the system.more than twice the capacity of TDMA),whereas the opposite might be true if the QoS requirement is relaxed to allow packet loss rates of up to10%.A possible way to improve matters for TDMA might be to reintroduce some degree of frequency isolation,e.g.,not reusing the same spectrum in all cells.We believe that a more ef?cient system strategy would be to ac-cept relatively high packet loss rates at the access layer,coupled with some smart scheduling strategies for ef?cient retransmis-sion,as was proposed in[7].Another alternative might be to dy-namically assign channels among different cells,which involves considerably more complexity but can potentially prevent worst-case occurrences,thereby greatly improving the overall perfor-mance.Finally,more advanced signal processing techniques (e.g.,smart antenna arrays)can also be used to reduce the effect of interference.Due to the already considerable complexity of our physical-layer study,we have not addressed these aspects, which are left for future efforts.We make a note here that although the chosen value of the spreading gain is50,the number of admitted users could be much higher since the user activity is small(equal to10%in this case).

Figures7illustrates the performance of the TDMA and CDMA systems with Type3traf?c,i.e.,packet traf?c users in heavy load.Plotted as a function of the expected number of users per cell is the saturation throughput,which is the amount of traf?c that the network can carry with no delay constraints.For a given number of admitted users,,and a given transmit probability ,the probability of success is found by simula-tion.Note that,in computing this probability of success,all possible channel conditions are considered.The service rate is then maximized with respect to the transmit probability.The value of which achieves this maximum also achieves the saturation throughput as explained in Section2.It is to be noted that,since the metrics thus computed are averages (the averaging being done over all possible channel conditions), there are no QoS objectives de?ned for this traf?c class.The effects of various parameters on the CDMA system are shown in Figure7.From Figure7,it is seen that the TDMA system achieves a higher saturation throughput and a better maximum achievable service rate than does the CDMA system.This is not surprising since,without any delay constraints,retransmission with time diversity is expected to be more bandwidth ef?cient than the a priori protection provided by bandwidth spreading[7] (note,in fact,that in CDMA,bandwidth is spread even when it is not needed,i.e.,when there is little interference).

In Figure7,it is seen that the TDMA throughput?rst in-creases with the number of users per cell,,but then asymptot-ically decreases as becomes large.This is due to the fact that there is no intra-cell contention among the TDMA users for low values of.However,as increases,a user’s signal would be subject to intra-cell interference in addition to inter-cell in-terference,causing an overall throughput reduction.Thus,when the per-user transmission probability is chosen to maximize the saturation throughput,adding users eventually causes an asymp-totic reduction in throughput.

Finally,Figure8shows results of mean delay for VBR Type4 traf?c.When analyzing the performance of this traf?c class,we assumed that the co-channel interference and multipath fading experienced by a packet vary independently from one transmis-

sion attempt to another.As discussed in Section2,this may be

a reasonable assumption if?ne power control is used and in the presence of a suf?cient degree of randomization of the trans-

mission attempts.The mean delay is minimized with respect to

the transmit probability.From queueing theory,the minimum mean delay is achieved when is chosen so as to maximize the

throughput.Thus,as in the case of Type3traf?c,one might ex-pect the TDMA mean delay performance to be better than that of CDMA.Figure8compares the mean delay performance of CDMA and TDMA.It is seen that a TDMA scheme using a rate 1/2code can admit approximately twice as many remote-users as may be admitted in a CDMA scheme using a rate1/2code before the system becomes unstable.Other results,not shown here,indicate that reducing the arrival rate to a remote user’s queue,,by half approximately doubles the number of ad-missible users,as expected.

IV C ONCLUSIONS AND F UTURE W ORK

In this work we have compared the performances of CDMA and TDMA systems in a packet switched wireless network.Dif-ferent traf?c classes,requiring different QoS metrics,have been independently considered.By means of analysis and simula-tions,the capacity of the network,stated in terms of the maxi-mum number of users admissible to a geographical region such that some QoS objective can be guaranteed,was found.Results obtained under a speci?c set of assumptions show that the rela-tive performance of CDMA and TDMA,expressed in terms of admissible number of users,largely depends on the QoS objec-tives set at the radio access level.As a general result,TDMA may be used in conjunction with protocol stacks which are able to recover from relatively high packet loss rates on the air inter-face,whereas CDMA should be used when small packet error rates at the radio access level are necessary.

While the results obtained in this work provide some valu-

able insight about the performance of the TDMA and CDMA schemes in a wireless packet environment,further study is re-quired in order to draw more?rm conclusions while also re-laxing some of the simplifying assumptions made here.In par-ticular,extending the effect of this study to higher layers in the protocol stack(e.g.,data-link error control)may enable a clearer assessment of the performance of the whole system.Also,this work is limited to the independent study of different traf?c classes. Study of co-existing multiple traf?c classes with differing QoS requirements needs further attention.Also,use of sectorized or array antennas,which may yield signi?cant performance im-provements in both TDMA and CDMA,also merits future in-vestigation.

Finally,while the objective of the paper was to compare CDMA

with TDMA with a frequency re-use factor of1,we recognize that a comparison with multiple frequency TDMA may be ap-propriate.However,it is beyond the scope of this preliminary work.We point out that since we have compared the schemes with a varying number of users,using multiple frequencies(or using frequency hopping)will cause the interference that is ex-perienced by a transmitting user due to simultaneously trans-mitting interferers to be reduced.This may be represented as a reduction in the number of interfering users or,equivalently,as a capacity increase.However,we note that this capacity increase (in terms of number of users per cell)is actually achieved at the expense of a capacity loss due to the use of a frequency reuse plan.In a packet-switched situation it is likely that not using full frequency reuse will lead to worse results.

A E STIMATION OF SIR IN THE CDMA SYSTEM

A Signal Component and Self Interference

Let a single user,transmit a signal given by:

(8) which passes through a channel with a complex impulse re-sponse.Let denote the in-put to the receiver(i.e.,),which con-sists of a matched?lter with impulse response,and let be the output of the matched?lter,given by

inphase quadrature.

The output of the matched?lter is sampled at time:

(9) Also,

(10)

where,.Denoting

by,we get:

(11)

Using a subscript to represent equivalent terms for the quadra-ture channel,Equation(11)can be written as:

(12)

Notice that all the terms in the above expression are real and hence,is a real quantity.The notation

is used hence forth.The?rst term of Equation(12)repre-sents the signal component and the second term represents self noise due to multipath propagation.Since and take the values+1and-1with equal probability and are assumed to be statistically independent of each other(ideal spread spectrum

modulation),the expected value of the self noise is zero,and its variance is given by:

.

In a manner similar to the de?nition of let us de?ne:

(17) Further,let

(18) Then,we write Equation(16)as:

(19) and it can be shown(with some algebraic simpli?cations)that

(22)

B E STIMATION OF SIR IN THE TDMA SYSTEM

Let a given user,transmit a signal such that a single bit from this user is given by:

(23) iLet denote the input to the receiver.Then,

where is the impulse response of the complex Gaussian channel through which the signal passes. The receiver is assumed to consist of a matched?lter whose impulse response is given by.The output of the matched ?lter is sampled at time.The output consists of the sig-nal,the multiple access interference,and an intersymbol interference(ISI)contribution from bits that precede and follow .At the output of the matched?lter,let the response of our given user at the output of the matched?lter,(consisting of the intended signal and the ISI)be denoted by.Then,at the sample time,

(24) Expanding Equation(24),we get:

(25) where

is the bit time.

is the maximum number of bits which contribute to the intersymbol interference.This number is a function of the delay spread of the channel.

We are interested in only real part of the signal appearing at the output of the receiver.It can then be shown that the signal power is given by

where,

and,

The ISI noise component is given by

Note that the mean value of the ISI is zero.It can be shown that the variance of the ISI is given by:

(26)

Since,for the signal,we are considering a known channel im-pulse response(as in the CDMA case),is deterministic. To calculate the multiple access interference,we denote user’s signal by

and the impulse response of the channel through which this sig-nal passes by.It can then be shown that total the multiple access interference due to the presence of interfering users is given by

(27)

where is the random variable representing the multiple access interference.

Using Equations25,26and27,and by considering the effects of pathloss and shadowing,the SIR can be expressed as:

[14]B.Glance and L.J.Greenstein,“Frequency-Selective Fad-

ing Effects in Digital Mobile Radio with Diversity Com-bining”,IEEE https://www.wendangku.net/doc/9e10257801.html,mun.,V https://www.wendangku.net/doc/9e10257801.html,-31,No.9.pp 1085-1094,September1983.

[15]D.Bertsekas and R.Gallager,Data Networks,Englewood

Cliffs,N.J.,Prentice-Hall,1992.

[16]S.Lin and D.J.Costello Jr.,Error Control Coding:

fundamentals and applications,Englewood Cliffs,N.J., Prentice-Hall,1983.

[17]S.V.Krishnamurthy et al.,“A Capacity Comparison of

TDMA and CDMA for Broadband Wireless Packet Ac-cess”,Center for Wireless Communications Technical Re-port,University of California,San Diego1997.

Srikanth V.Krishnamurthy(S’94–M’00)received

his Ph.D.degree in Electrical and Computer Engi-

neering from the University of California,San Diego,

La Jolla,in1997.He is currently an Assistant Pro-

fessor of Computer Science and Engineering at the

University of California,Riverside.Prior to joining

UC Riverside,from1998to2000,he was a Research

Staff Scientist at the Information Sciences Labora-

tory,HRL Laboratories,LLC,Malibu,CA,where he

was leading various mobile wireless and satellite net-

working projects including the DARPA Next Genera-tion Internet and the Small Unit Operations Projects.He is also a Co-Principal Investigator on the DARPA Fault Tolerant Networks Project at UC Riverside. His research interests span CDMA and TDMA technologies,medium access control for satellite and wireless networks,routing and multicasting in wire-less networks,power management and the use of smart antennas in wireless networks,quality-of-service for the Internet and security.He was the Technical Co-Chair for the Workshop on Satellite Broadband Information Services(WOS-BIS)held in conjunction with Globecom in1999and has been on the technical program committees for IEEE INFOCOM,ACM Mobihoc and IEEE ICC.He was also the local arrangements chair for ACM Mobihoc2001and IEEE ICNP 2001.E-Mail:krish@https://www.wendangku.net/doc/9e10257801.html,

Anthony S.Acampora(S’68–M’68–SM’86–F’88)

is a Professor of Electrical and Computer Engineer-

ing at the University of California,San Diego,and

is involved in numerous research projects addressing

various issues at the leading edge of telecommunica-

tions networks,including the Internet,ATM,broad-

band wireless access,network management and dense

wavelength division multiplexing.From1995through

1999,he was Director of UCSD’s Center for Wire-

less Communications,responsible for an industrially

funded research effort which included circuits,signal processing,smart antennas,basic communication theory,wireless telecommu-nication networks,infrastructure for wireless communications,and software for mobility.Since early1997,he has been an advisor to the Board of Directors at Wireless Facilities,Inc.,a San Diego company devoted to telecommunications outsourcing,and in March,1998,he co-founded AirFiber Inc.,a San Diego-based company involved in the development and marketing of broadband free space optical networking equipment for cellular and local exchange carriers. Prior to joining the faculty at UCSD in1995,he was Professor of Electrical Engineering at Columbia University and Director of Center for Telecommuni-cations Research,a national engineering research center.He joined the faculty at Columbia in1988following a20-year career at AT&T Bell Laboratories,most of which was spent in basic research where his research interests included ra-dio and satellite communications,local and metropolitan area networks,packet switching,wireless access systems,and lightwave networks.His most recent position at Bell Labs was Director of the Transmission Technology Laboratory where he was responsible for a wide range of projects,including broadband networks,image communications and digital signal processing.At Columbia, he was involved in research and education programs concerning broadband net-works,wireless access networks,network management,optical networks and multimedia applications.He received his Ph.D in Electrical Engineering from the Polytechnic Institute of Brooklyn and is Fellow of the IEEE and a former member of the IEEE Communication Society Board of Governors.Professor Acampora has published over160papers,holds30patents,and has authored a book entitled”An Introduction to Broadband Networks:MANs,ATM,B-ISDN, Self Routing Switches,Optical Networks,and Network Control for V oice,Data, Image and HDTV Telecommunications”.He sits on numerous telecommunica-tions advisory committees and frequently serves as a consultant to government and industry.E-Mail:acampora@https://www.wendangku.net/doc/9e10257801.html,

Michele Zorzi(S’89–M’95–SM’98)was born in Venice,

Italy,in1966.He received the Laurea Degree and the

Ph.D.in Electrical Engineering from the University

of Padova,Italy,in1990and1994,respectively.Dur-

ing the Academic Year1992/93,he was on leave at

the University of California,San Diego(UCSD),at-

tending graduate courses and doing research on mul-

tiple access in mobile radio networks.In1993,he

joined the faculty of the Dipartimento di Elettron-

ica e Informazione,Politecnico di Milano,Italy.Af-

ter spending three years with the Center for Wireless Communications at UCSD,in1998he joined the School of Engineering of the Universit`a di Ferrara,Italy,where he is currently a Professor.His present re-search interests include performance evaluation in mobile communications sys-tems,random access in mobile radio networks,and energy constrained com-munications protocols.?Dr.Zorzi currently serves on the Editorial Boards of the IEEE Personal Communications Magazine,the ACM/URSI/Baltzer Journal

of Wireless Networks,the IEEE Transactions on Wireless Communications,and the WILEY Journal of Wireless Communications and Mobile Computing.He is also guest editor for special issues in the IEEE Personal Communications Maga-zine(Energy Management in Personal Communications Systems)and the IEEE Journal on Selected Areas in Communications(Multi-media Network Radios).

E-mail:zorzi@ing.unife.it

In CDMA each burst occupies

Fig.1.Slot structures for the(a)CDMA and(b)TDMA schemes

5

10

Expected number of users per cell

10

-3

10

-2

10

-1

10

P r o b a b i l i t y o f o u t a g e

Fig.2.CBR Traf?c:Effects of Power Control.No coding,

,

.

05

101520

25

Expected number of users per cell

10

-3

10

-2

10

-1

10

P r o b a b i l i t y o f o u t a g e

Fig.3.CBR Traf?c:Effects of Speech Activity Detection (SAD).No coding,,

.

5101520

Expected number of users per cell

10

-3

10

-2

10

-1

10

P r o b a b i l i t y o f o u t a g e

Fig.4.CBR Traf?c,CDMA:Performance of Different Codes.Fine power control,

,

,no SAD.

Expected number of users per cell

10

-3

10

-2

10

-1

10

P r o b a b i l i t y o f o u t a g e

Fig.5.CBR Traf?c:Comparison of CDMA and TDMA schemes.Fine power control,,

,no SAD.

50100150200

Expected number of users per cell

10

-3

10

-2

10

-1

10

P [p a c k e t l o s s r a t e > x ]

Fig.6.Packet Traf?c with no queueing allowed:Comparison of CDMA and TDMA schemes.Fine power control,rate 1/2code,,

,

.

20406080100

Expected number of users per cell

0.0

0.2

0.4

0.6

0.8

1.0

M a x i m u m a c h i e v a b l e t h r o u g h p u t

Fig.7.Maximum Saturation throughput:CDMA and TDMA.Fine power control,rate 1/2code,

,

.

50100150200

Expected number of users per cell

1

2

3

45

M e a n d e l a y (s l o t s )

Fig.8.Packet Traf?c with mean delay constraints.Fine power control,rate 1/2code,

,

移动通信原理与系统(北京邮电出版社)课后答案

第一章概述 1．1简述移动通信的特点： 答：①移动通信利用无线电波进行信息传输； ②移动通信在强干扰环境下工作； ③通信容量有限； ④通信系统复杂； ⑤对移动台的要求高。 1．2移动台主要受哪些干扰影响？哪些干扰是蜂窝系统所特有的？ 答：①互调干扰； ②邻道干扰； ③同频干扰；（蜂窝系统所特有的） ④多址干扰。 1．3简述蜂窝式移动通信的发展历史，说明各代移动通信系统的特点。 答：第一代（1G）以模拟式蜂窝网为主要特征，是20世纪70年代末80年代初就开始商用的。其中最有代表性的是北美的AMPS（Advanced Mobile Phone System）、欧洲的TACS（Total Access Communication System）两大系统，另外还有北欧的NMT 及日本的HCMTS系统等。 从技术特色上看，1G以解决两个动态性中最基本的用户这一重动态性为核心并适当考虑到第二重信道动态性。主要是措施是采用频分多址FDMA方式实现对用户的动态寻址功能，并以蜂窝式网络结构和频率规划实现载频再用方式，达到扩大覆盖服务范围和满足用户数量增长的需求。在信道动态特性匹配上，适当采用了性能优良的模拟调频方式，并利用基站二重空间分集方式抵抗空间选择性衰落。 第二代（2G）以数字化为主要特征，构成数字式蜂窝移动通信系统，它于20世纪90年代初正式走向商用。其中最具有代表性的有欧洲的时分多址（TDMA）GSM（GSM原意为Group Special Mobile，1989年以后改为Global System for Mobile Communication）、北美的码分多址（CDMA）的IS-95 两大系统，另外还有日本的PDC 系统等。 从技术特色上看，它是以数字化为基础，较全面地考虑了信道与用户的二重动态特性及相应的匹配措施。主要的实现措施有：采用TDMA（GSM）、CDMA（IS-95）方式实现对用户的动态寻址功能，并以数字式蜂窝网络结构和频率（相位）规划实现载频（相位）再用方式，从而扩大覆盖服务范围和满足用户数量增长的需求。在对信道动态特性的匹配上采取了下面一系列措施： （1）采用抗干扰性能优良的数字式调制：GMSK（GSM）、QPSK（IS-95），性能优良的抗干扰纠错编码：卷积码（GSM、IS-95）、级联码（GSM）； （2）采用功率控制技术抵抗慢衰落和远近效应，这对于CDMA方式的IS-95尤为重要； （3）采用自适应均衡（GSM）和Rake 接收（IS-95）抗频率选择性衰落与多径干扰； （4）采用信道交织编码，如采用帧间交织方式（GSM）和块交织方式（IS-95）抗时间选择性衰落。 第三代（3G）以多媒体业务为主要特征，它于本世纪初刚刚投入商业化运营。其中最具有代表性的有北美的CDMA2000、欧洲和日本的WCDMA及我国提出的TD-SCDMA三大系统，另外还有欧洲的DECT及北美的UMC-136。 从技术上看，3G 是在2G 系统适配信道与用户二重动态特性的基础上又引入了业务的动态性，即在3G 系统中，用户业务既可以是单一的语音、数据、图像，也可以是多媒体业务，且用户选择业务是随机的，这个是第三重动态性的引入使系统大大复杂化。所以第三代是在第二代数字化基础上的、以业务多媒体化为主要目标，全面考虑并完善对信道、用户二重动态特性匹配特性，并适当考虑到业务的动态性能，尽力采用相应措施予以实现的技术。其主要实现措施有： （1）继续采用第二代（2G）中所采用的所有行之有效的措施； （2）对CDMA扩频方式应一分为二，一方面扩频提高了抗干扰性，提高了通信容量；另一方面由于扩

局域网点对点通信软件设计与实现

《网络编程技术》 课程设计报告 课程设计题目：局域网点对点通信软件与实现作者所在系部：计算机科学与工程系 作者所在专业：网络工程 作者所在班级： 作者姓名： 作者学号： 指导教师姓名： 完成时间： 2013年07月10日

课程设计任务书

摘要 所谓网络中的点对点通信是实现网络上不同计算机之间，不经过任何中继设备而直接交换数据或服务的一种技术。由于允许网络中任何一台计算机可以直接连到网络中的其他计算机，并与之进行数据交换，这样既可以消除中间环节，也使得网络上的沟通变的更加容易、更加直接。本文介绍的是一种是用Winsock编程技术，基于TCP/IP协议的、面向连接的流式套接字网络通信编程设计。 局域网即时通讯软件使用TCP协议作为传输层的协议，采用点对点模式服务，不需要服务器支持，使局域网用户的使用更加方便和高效。它可以实现局域网用户的自动检测，用户间文本信息的交流，文件的传输等功能。 本系统使用Visual Studio 2010作为开发工具，将.NET中的一些技术运用到系统中关键词：点对点；TCP/IP；Socket；UDP；P2P

目录 摘要 (2) 目录 (3) 第1章绪论 (4) 1.1课题研究现状分析 (4) 1.2选题的目的及意义 (4) 第2章系统需求分析 (5) 2.1 问题的提出 (5) 2.2 系统的设计目标 (5) 第3章系统总体设计 (6) 3.1系统功能设计 (6) 3.2功能模块的说明 (7) 3.2.1初始化（广播用户信息） (7) 3.2.2用户列表管理 (7) 3.2.3文本信息传输 (7) 3.2.4文件传输 (7) 3.2.5发送心跳包 (7) 第4章系统实现 (8) 4.1初始化模块的设计和实现 (8) 4.1.1监听端口 (8) 4.2 广播消息 (8) 4.3 文本消息的发送和接收 (9) 4.4 文件的发送和接收 (12) 4.5发送心跳包 (14) 第5章课程设计总结 (16) 5.1 主要问题及解决办法 (16) 5.2 课程设计体会 (16) 5.3 自我评定 (16) 参考文献 (17)

《数字通信原理(第三版)》教材课后习题答案

《数字通信原理》习题解答 第1章 概述 1-1 模拟信号和数字信号的特点分别是什么? 答：模拟信号的特点是幅度连续；数字信号的特点幅度离散。 1-2 数字通信系统的构成模型中信源编码和信源解码的作用是什么?画出话音信号的基带传输系统模型。 答：信源编码的作用把模拟信号变换成数字信号，即完成模/数变换的任务。 信源解码的作用把数字信号还原为模拟信号，即完成数/模变换的任务。 话音信号的基带传输系统模型为 1-3 数字通信的特点有哪些? 答：数字通信的特点是： （1）抗干扰性强，无噪声积累； （2）便于加密处理； （3）采用时分复用实现多路通信； （4）设备便于集成化、微型化； （5）占用信道频带较宽。 1-4 为什么说数字通信的抗干扰性强，无噪声积累? 答：对于数字通信，由于数字信号的幅值为有限的离散值(通常取二个幅值)，在传输过程中受到噪声干扰，当信噪比还没有恶化到一定程度时，即在适当的距离，采用再生的方法，再生成已消除噪声干扰的原发送信号，所以说数字通信的抗干扰性强，无噪声积累。 1-5 设数字信号码元时间长度为1s μ，如采用四电平传输，求信息传输速率及符号速率。 答：符号速率为 Bd N 661010 11===-码元时间 信息传输速率为 s Mbit s bit M N R /2/1024log 10log 6 262=?=?== 1-6 接上例，若传输过程中2秒误1个比特，求误码率。

答：76105.210 221)()(-?=??==N n P e 传输总码元发生误码个数 1-7 假设数字通信系统的频带宽度为kHz 1024，可传输s kbit /2048的比特率，试问其频带利用率为多少Hz s bit //? 答：频带利用率为 Hz s bit Hz s bit //2101024102048)//3 3 =??==（频带宽度信息传输速率η 1-8数字通信技术的发展趋势是什么？ 答：数字通信技术目前正向着以下几个方向发展：小型化、智能化，数字处理技术的开发应用，用户数字化和高速大容量等。 第2章 数字终端编码技术 ——语声信号数字化 2-1 语声信号的编码可分为哪几种？ 答：语声信号的编码可分为波形编码（主要包括PCM 、ADPCM 等）、参量编码和混合编码（如子带编码）三大类型。 2-2 PCM 通信系统中A ／D 变换、D ／A 变换分别经过哪几步? 答：PCM 通信系统中A ／D 变换包括抽样、量化、编码三步； D ／A 变换包括解码和低通两部分。 2-3 某模拟信号频谱如题图2-1所示，（1）求满足抽样定理时的抽样频率S f 并画出抽样信号的频谱（设M S f f 2=）。（2）若,8kHz f S =画出抽样信号的频谱，并说明此频谱出现什么现象? 题图2-1

点对点和点对多点语音通信的应用

听《多点对多点通信》讲座有感之《点对点和点对多点语音通信的应用》

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远距离点对点数字通信系统设计大学论文

通信原理三级项目 班级：姓名： 学号： 指导教师： 教务处

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目录 1. 前言 (1) 1.1选题的意义和目的 (1) 1.2通信系统及其仿真技术 (2) 3. 现代通信系统的介绍 (3) 3.1通信系统的一般模型 (3) 3.2模拟通信系统模型和数字通信系统模型 (3) 3.2.1 模拟通信系统模型 (3) 3.2.2 数字通信系统模型 (4) 3.3模拟通信和数字通信的区别和优缺点 (5) 4. 通信系统的仿真原理及框图 (8) 4.1模拟通信系统的仿真原理 (8) 4.1.1 DSB信号的调制解调原理 ...................... 错误！未定义书签。 4.2数字通信系统的仿真原理 (9) 4.2.1 ASK信号的调制解调原理 (9) 5. 通信系统仿真结果及分析 (11) 5.1模拟通信系统结果分析 (11) 5.1.1 DSB模拟通信系统 (11) 5.2仿真结果框图 (11) 5.2.1 DSB模拟系统仿真结果 ........................ 错误！未定义书签。 5.3数字通信系统结果分析 (12) 5.3.1 ASK数字通信系统 (13) 5.4仿真结果框图 (13) 5.4.1 ASK数字系统仿真结果 (13) III

现代通信原理与技术第三版课后_思考题答案

第一章 1.1 以无线广播和电视为例，说明图 1-1 模型中的信息源，受信者及信道包含的具体内容是什么？ 在无线电广播中，信息源包括的具体内容为从声音转换而成的原始电信号，收信者中包括的具体内容就是从复原的原始电信号转换乘的声音；在电视系统中，信息源的具体内容为从影像转换而成的电信号。收信者中包括的具体内容就是从复原的原始电信号转换成的影像；二者信道中包括的具体内容分别是载有声音和影像的无线电波 1.2 何谓数字信号，何谓模拟信号，两者的根本区别是什么？ 数字信号指电信号的参量仅可能取有限个值；模拟信号指电信号的参量可以取连续值。他们的区别在于电信号参量的取值是连续的还是离散可数的。 1.3 何谓数字通信，数字通信有哪些优缺点？ 传输数字信号的通信系统统称为数字通信系统； 优缺点： 1.抗干扰能力强；2.传输差错可以控制；3.便于加密处理，信息传输的安全性和保密性越来越重要，数字通信的加密处理比模拟通信容易的多，以话音信号为例，经过数字变换后的信号可用简单的数字逻辑运算进行加密，解密处理；4.便于存储、处理和交换；数字通信的信号形式和计算机所用的信号一致，都是二进制代码，因此便于与计算机联网，也便于用计算机对数字信号进行存储，处理和交换，可使通信网的管理，维护实现自动化，智能化；5. 设备便于集成化、微机化。数字通信采用时分多路复用，不需要体积较大的滤波器。设备中大部分电路是数字电路，可用大规模和超大规模集成电路实现，因此体积小，功耗低；6. 便于构成综合数字网和综合业务数字网。采用数字传输方式，可以通过程控数字交换设备进行数字交换，以实现传输和交换的综合。另外，电话业务和各种非话务业务都可以实现数字化，构成综合业务数字网；缺点：占用信道频带较宽。一路模拟电话的频带为 4KHZ 带宽，一路数字电话约占64KHZ。 1.4 数字通信系统的一般模型中的各组成部分的主要功能是什么？ 数字通行系统的模型见图1-4 所示。其中信源编码与译码功能是提高信息传输的有效性和进行模数转换；信道编码和译码功能是增强数字信号的抗干扰

点对点通信实验步骤2017

基于CAsyncSocket类的点对点通信客户机创建流程 ●通信流程： 1.服务器点击“监听”按钮开始监听，实现Create和Listen函数 2.客户机点击“连接”按钮进行连接，实现Connect函数 3.服务器端接受连接，并触发onAccept事件，实现函数Aeecpt 4.客户端或者服务器端点击“发送”按钮，发送文本框的数据 5.服务器端或者客户端接收数据，OnReveive事件被触发，实现函数Receive 6.客户端或者服务器端点击“断开”，执行函数close，触发另一端的onClose 事件 自定义类获取对话框指针的方法 1.先在CMyDialog.cpp中声明一个全局变量CMyDialog* pDlg; 2在OnInitDialog()初始化的时候，pDlg = this; 3.在自定义类使用的时候，在自定义的类的Cpp中添加extern CMyDialog* pDlg; 4.在自定类中使用pDlg->yourfunction(); ●编程过程： 客户端： 1、创建MFC应用程序，勾选windows socket选项，如创建工程名为client，自动创建类 CClientAPP和CClientDlg，并生成相应的源文件（.cpp）和头文件(.h)。APP代表应用程序。 Dlg代表对话框 2、布置界面如下图所示

3、建立类向导，给文本编辑框，列表框定义变量名及类型 4、插入基于CAsyncSocket的类，如取名clientsock，确定后类视图下右键单击类并载入虚函数onReceive(),onClose()，如果是服务器端还要加载onAccept 5、程序的各个类之间建立联系，具体步骤： 5.1对话框界面与套接字建立连接。在ClientDlg.h文件中将“clientsock.h”文件包含进来，使其能够访问套接字，代码为#include”clientsocket.h”;并添加成员变量m_clientsock，代码clientsock m_clientsock;

移动通信原理与系统(总结)

第一、二章 1、900 MHz 频段： 890~915 MHz （移动台发、基站收）—上行 935~960 MHz （基站发、移动台收）—下行 2、移动通信的工作方式：单工通信、双工通信、半双工通信 3、单工通信： （1）定义：通信双方电台交替地进行收信和发信。 （2）方式：根据通信双方是否使用相同的频率，单工制又分为同频单工和双频单工。 4、双工通信定义：通信双方均同时进行收发工作。即任一方讲话时，可以听到对方的话音。有时也叫全双工通信。 5、半双工通信：通信双方中，一方使用双频双工方式，即收发信机同时工作；另一方使用双频单工方式，即收发信机交替工作。 6、移动通信的分类方法： （1）按多址方式：频分多址（FDMA ）、时分多址（TDMA ）和码分多址（CDMA ） （2）按业务类型：电话网、数据网和综合业务网。 （3）按工作方式：同频单工、双频单工、双频双工和半双工。 7、三种基本电波的传播机制：反射、绕射和散射。 8、阴影衰落定义：移动无线通信信道传播环境中的地形起伏、建筑物及其它障碍物对电波传播路径的阻挡而形成的电磁场阴影效应。阴影衰落的信号电平起伏是相对缓慢的，又称为慢衰落。 9、多普勒频移公式：fd=v *cos α/λ v ：移动速度 λ：波长 α：入射波与移动台移动方向之间的夹角。 v/λ=fm ：最大多普勒频移 移动台朝向入射波方向运动，则多普勒频移为正（接收信号频率上升），反之若移动台背向入射波方向运动，则多普勒频移为负（接收信号频率下降）。 10、多径衰落信道的分类： （1）由于时间色散导致发送信号产生的平坦衰落和频率选择性衰落。 （2）根据发送信号与信道变化快慢程度的比较，也就是频率色散引起的信号失真，可将信道分为快衰落信道和慢衰落信道。 11、平坦衰落信道的条件可概括为：Bs<> 12、产生频率选择性衰落的条件：Bs>Bc;Ts< 13、信号经历快衰落的条件：Ts>Tc ;Bs>B D 15、衰落率定义：信号包络在单位时间内以正斜率通过中值电平的次数，即包络衰落的速率与发射频率，移台行进速度和方向以及多径传播的路径数有关。 16 v ：——运动速度（km/h ）f ：——频率（MHz ）A ：——平均衰落（Hz ） 17、衰落深度：信号有效值与该次衰落的信号最小值的差值。 18、电平通过率定义：单位时间内信号包络以正斜率通过某一规定电平值R 的平均次数。描述衰落次数的统计规律。 深度衰落发生的次数较少，而浅度衰落发生得相当频繁。 19、平均电平通过率表达式： 其中f m ：——最大多普勒频率 ρ=R/R min 其中Rmin= 为信号有效值，R 为规定电平 T τσ T τσ

点对点数字通信系统设计说明

通信原理三级项目 班级：通信工程2班 姓名： 学号： 指导教师： 教务处 2016年 5月

远距离点对点数字通信系统设计 （燕山大学信息科学与工程学院） 摘要：本文讨论进行了远距离点对点数字通信系统的设计，着重讨论了模拟信号数字化的过程，其中包含了为了提高系统性能进行的信源编码技术和信道编码技术，我采用了HDB3码克服连0问题，利用奇偶监督码和差错重传机制控制误码率。另外，讨论了数字调制技术的实现，本文采用最小频移键控调制和解调技术，并讨论了在高斯白噪声信道条件下的此方法的可靠性和有效性。 关键词：脉冲编码调制，HDB3码，奇偶监督码，MSK调制，高斯白噪声，MATLAB 仿真

目录 1.通信系统概述 (3) 1.1一般通信系统模型 (3) 1.2数字通信系统模型 (4) 1.3远距离语音通信系统 (4) 2.信号数字化 (5) 2.1信号的抽样 (5) 2.1.1抽样定理 (5) 2.1.2脉冲幅度调制PAM (5) 2.2信源编码 (7) 2.2.1十三折线法 (7) 2.2.2脉冲编码调制PCM (9) 2.3信道编码 (10) 2.3.1 HDB3码 (10) 2.3.2奇偶监督码 (11) 3.调制与解调 (11) 3.1 MSK调制 (11) 3.1.1 MSK调制原理 (12) 3.1.2 MSK调制 (13) 3.2 MSK解调 (14) 4.信道描述 (15) 5.系统总体设计 (16) 附录 MATLAB实现代码 (17)

1.通信系统概述 1.1一般通信系统模型 一般作为一个通信系统都由发送端和接收端两部分组成，而发送端则分为信息源和发送设备两部分，接收端与其对应的有接收端和受信者两部分，发送端和接收端之间则是我们信号传输所需要经过的信道，信号在信道中传输时会有噪声的混入，这也是我们的通信系统性能讨论的终点。 图1-1 一般通信系统 信息源是把各种原始消息转换成原始电信号的设备，它通过各种物理转换的方法从自然界中采集信息并把它们转换成相应的电信号，从而便于我们通过电子设备对其进行进一步的处理。受信者则是把接受到的电信号还原成自然界中信息的设备。 发送设备是通过对采集到的原始电信号进行一系列的处理把它变成适合于远距离传输的信号。在模拟传输系统中包括放大、滤波、模拟调制等过程；在数字传输系统中则包含编码、加密、数字调制等过程。接收设备则是上述过程的逆过程，将信道中传输的信号还原成易于处理的直接电信号。 信道是从发送设备到接收设备之间信号传输的物理煤质，分为无线信道和有限信道两大类，每种信道的特点不同，应用场合也不相同。 噪声源是笼统的一个说法，它集中表示分布于通信系统中的各处的噪声。

数字通信原理复习

复习题 名词：同步, 映射, 抽样，量化, DPCM, 汉明码, 复用, 定位，时分多路复用，正码速调整，同步复接，异步复接 问答： 1.数字信号和模拟信号的特点。 2.数字信号的有效性和可靠性指标及其计算方法。 3.为什么数字通信的抗干扰性强，无噪声积累? 4.低通和带通信号抽样定理。 5.回答均匀量化与非均匀量化的特点，说明为什么引入非均匀量化. 6.说明码的抗干扰能力与最小码距的关系. 7.什么叫PCM零次群? PCM30/32一至四次群的速率和接口码型分别是什么? 8.帧同步的目的是什么? PCM30/32系统的帧同步码型为何? 9.PCM帧同步系统处理流程图。 10.PCM30/32系统帧结构。 11.PCM帧同步系统中，前方保护和后方保护分别是指什么？其各自防止的现 象是什么？ 12.PCM一次群到异步复接二次群，与同步复接的区别。 13.简述SDH通信系统的特点。 14.SDH帧结构分哪几个区域? 各自的作用是什么? 15.SDH 网的速率等级有哪些? 16.SDH 中复用的概念是什么? 17.SDH 传送网的基本物理拓扑有哪几种? 18.SDH数字通信系统的特点是什么？ 19.画出SDH帧结构，计算出STM-N各个区域的速率大小 20.SDH网同步方式和时钟工作方式。 21.G.707 SDH复用结构。 计算方面： 1.A律13折线编解码，7/11变换； 2.带通信号的抽样及其计算，抽样后信号的频谱形式； 3.循环码计算，循环码多项式，监督矩阵和生成矩阵

4.SDH帧结构中各个信息结构速率的计算 5.系统循环码的多项式计算。 1. 某设备未过载电平的最大值为4096mv，有一幅度为2000mv的样值通过A律13折线逐次对分编码器，写出编码器编码过程及输出的8位PCM码。 2. PCM30/32路的帧长，路时隙宽，比特宽，数码率各为多少？ 3. 设数字信号码元时间长度为05sμ，如采用八电平传输，求信息传输速率及符号速率；若传输过程中2秒误1个比特，求误码率。 4. 为什么同步复接要进行码速变换？ 答：对于同步复接，虽然被复接的各支路的时钟都是由同一时钟源供给的，可以保证其数码率相等，但为了满足在接收端分接的需要，还需插入一定数量的帧同步码；为使复接器、分接器能够正常工作，还需加入对端告警码、邻站监测及勤务联络等公务码（以上各种插入的码元统称附加码），即需要码速变换。 5. 异步复接中的码速调整与同步复接中的码速变换有什么不同？ 答：码速变换是在平均间隔的固定位置先留出空位，待复接合成时再插入脉冲（附加码）； 而码速调整插入脉冲要视具体情况，不同支路、不同瞬时数码率、不同的帧，可能插入，也可能不插入脉冲（不插入脉冲时，此位置为原信息码），且插入的脉冲不携带信息。 6.由STM-1帧结构计算出①STM-1的速率。②SOH的速率。③AU-PTR的速率。 7.采用13折线A律编码，设最小的量化级为1个单位，已知抽样脉冲值为-95 单位。 (1)试求此时编码器输出码组，并计算量化误差（段内码用自然二进制码）；写出对应于该7位码（不包括极性码）的均匀量化11位码。 8.设数字信号码元时间长度为1sμ，如采用四电平传输，求信息传输速率及符 号速率。 答：符号速率为

数字通信原理与技术(第四版)复习笔记

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