GB2415871A - Dynamic subcarrier allocation in Multicarrier Spread Spectrum communication - Google Patents

Abstract

In Multi-Carrier (MC) Orthogonal Frequency Multiple Access (OFDMA) communication involving error correction coding, subcarriers are allocated to multiple users dynamically (124) by taking account of different user requirements of quality and bandwidth for different transmissions (eg. voice, low-resolution video, broadcast quality video etc.) and the accuracy of those channel models, in order to adapt the spread factor appropriately. Each mobile terminal (300a,b...) subcarrier's index and Signal to Noise Ratio (SNR) are fed back to the transmitter, and the base station estimates the average Pairwise Error Probability (PEP) produced by the decoder for a given candidate set of subcarrier frequency allocations and a predetermined pilot signal sequence, in order to calculate subcarrier allocations such that the bandwidth and quality requirements of all the terminals are met. Joint adaptation of pilot patterns and spreading factors may be necessary to achieve this. The channel coding can be Turbo (PEP = equation 8) or Convolutional (PEP = equation 13) coding, and different scheduling policies (122) can be implemented.

Description

241587 1

MULTICARRIER TRANSMISSION SYSTEMS

This invention relates to a multi-carrier transmission system in the context of wireless communications. More particularly, but not exclusively, the invention relates to channel coded multi-carrier systems, and methods of estimating the performance of such systems and allocating sub-carriers in such a system.

Backaround

lo Cellular services are now being used by millions of people every day and multimedia services are more and more in demand. The range of such multi-media services include for example short messaging, voice, data and video calls. Therefore, the required bit rate nor the services vary widely from about 1 kbps for paging up to several Mbps for video transmissions. In order to support such a wide range of data rates and an even wider range for future systems, highly flexible mobility management is required and thus even more complex network structures are needed.

Multi-carrier (MC) systems are today commonly used and are a great success, with the IEEE standardization of for example IEEE 802.1 1 a and g or 2() IEEE 802.16a, or the ETSI standardisaton of the Digital Audio Broadcasting (DAB) or the Digital Video Broadcasting (DVB-T) systems.

Multi-carrier modulation is a diversity data transmission technique where several subcarriers are used to transport the user data signal.

Moreover, the enhancement of robustness to multi-path, flexibility and reduced complexity compared to other powerful techniques such as code division multiple access (CDMA) systems, has led to the introduction of new radio air interfaces, such as multicarrier CDMA systems (MC-COMA). Such systems are for example described in A.Chouly et al, "Orthogonal multicarrier techniques applied to direct sequence spread spectrum CDMA systems", GLOBECOM '93 or in N. Yee et al., "Multicarrier CDMA in Indoor Wireless Radio Networks", Proceedings PIMRC'93, pp. 126-133. MC systems have therefore been considered as a good candidate for Next Generation Wireless Enablers, see for example WWRF, Book of Vision, Rask 4.7, "MultiCarrier Based Air interface", pp232, http://www.wireless-world-research. org/, MAGNET, http://www.telecom.cce.ntua.gr/magnet/ or WINNER, http://www.ist-winner.org/ Sixth Framework IST Project.

Next Generation air interface proposals involve thousands of subcarriers, and suggest user multiplexing by using Orthogonal Frequency Division Multiple Access systems (OFDMA), which has been proved to reduce intercell interference and significant packet transmission flexibility.

S. Kaiser and K. Fazel proposed a hybrid scheme in the paper "A flexible Spread-Spectrum Multi-Carrier Multple-Access System for Multi-Media 2() Applications, In Proc. IEEE PTMRC'97, pp. 1()0-104, namely MC-SS.

In MC-SS systems, frequency spreading of the user data is applied similarly to MC-CDMA systems. However, the orthogonality among the users is here obtained by multiplexing on distinct subcamers. in this way the advantage of the frequency diversity offered by the spreading is combined with the flexibility of user multiplexing offered by OFDMA systems, see for example the paper by S. Pietrzyk and G.J.M Janssen, "Multiuser Subcarrier Allocation for QoS Provision in the OFDMA Systems", IEEE VTC 2002, Vol.2, pp 1 077- 1 08 1.

Transmission systems can be further improved by the use of channel coding. Channel coding is a method of adding redundancy to information so that it can be transmitted over a degrading (fading and/or noisy) channel, and subsequently be checked and corrected for errors that occurred in transmission. Channel coding is especially beneficial for wireless and multimedia applications.

One example of a powerful coding scheme, the Turbo-Coding Scheme, was introduced by Berrou et al. in "Near Shannon limit error correcting coding and decoding: Turbo Codes", Proc. 1993, IEEE International Conference on Communications, May 1993, pp 1064-1070.

MC-SS transmission systems may be combined with Turbo-Coding, for example in Turbo-Coding System using Diversity, as described in T. Ohtsuki, and J. M. Kahn, "Performance of Turbo Codes with Two-Branch Receive Diversity and Correlated Fading", VTC 2000 and A. Ramesh et al., "Performance Analysis of'lurbo Codes on Fading Channels with Diversity Combining".

For future systems such as, for example, 4G mobile radio systems, Radio Resource Management (RRM) ---- i.e. channel allocation - needs to be optimised, such that the systems can cope with the multi-media communication requirements of multiple users.

These multiple users may have widely differing bandwidth requirements; for example, a first may require relatively small bandwidth voice communications, a second may require medium rate data communications, a third may require high bandwidth video communications, a fourth may require broadcast quality video, and so on. Each may also be prepared to accept a different level of quality (i.e. rate of errors). Allocating channels to each user has to take account of these differing requirements.

Transmission performance is usually determined by measuring the Bit Error Rate (BER) and the Signal-to-Noise Ratio (SNR) of the transmitted signal.

In a radio transmission system, interference sources will sporadically generate noise which will selectively affect different subcarriers. Also, transmission conditions will affect the response on each channel: for example, multi-path effects due to multiple reflections will affect both the gain and phase on each subcarrier differently. These effects arc experienced differently by different terminals, depending on their positions relative to the interference sources and reflectors. They will also vary over time, particularly where the terminals are themselves mobile. Thus, as conditions on different channels vary, they may need to be re-allocated to users during an existing commumcatons session.

The data link control (DLC) and the physical or kink layer may need to he jointly optimiscd. Such a new layer design may involve new scheduling policies which are based on parameters related to the physical layer, i.e. parameters as for example the frequency, link quality parameters such as the signal-to-noise ratio (SNR) or the bit error rate (BER), and also processes performed in the physical layer.

One such procedure is the so-called Dynamic Subcarrier Allocation (DSA), described in for example the paper by S. Pietrzyk and G.J.M Janssen, "Multiuser Subcarrier Allocation for QoS Provision in the OFDMA Systems", IEEE VTC 2002, Vol.2, pp1077-1081.

It is an aim of the present invention to provide a dynamic subcarrier allocation procedure for systems applying channel (i.e. error correcting) coding. It Is another aim of the present invention to allocate subcarriers to terminals of a channel coded multi-carrier system depending on the quality of service requirements of a particular user.

According to one aspect of the present invention, there is provided a method of communication, wherein multiple data streams are transmitted simultaneously and channel coded are used which are coded using a predetermined code, wherein radio resources are allocated according to an individual user's traffic requirement by dynamically allocating subcarriers, using a relationship for estimating the transmission performance taking account of the accuracy of the channel model to allocate the sub-carners.

In this way, a more 'realistic' estimate of the transmission performance, takmg into account imperfect knowledge of the transmission system Is used to allocate and manage the radio resources Preferably, the method is applied to turbo-coded multi-carrier spread spectrum systems.

In this way, the method may be further improved by using a joint adaptation strategy based on adapting the spread factor of the frequency spreading for allocating the sub-carriers.

According to another aspect of the present invention, there is provided a method of communication, wherein multiple data streams are transmitted simultaneously and channel coded are used which are coded using a predetermined code, and frequency spreading is applied, wherein radio resources are allocated according to an individual user's traffic requirement by dynamically allocating sub-carriers and a spreading factor of the frequency spreading, using a relationship for estimating the transmission performance taking account of the accuracy of the channel model and the spreading factor to allocate the sub-carriers.

According to another aspect of the present invention, there is provided a transmitter apparatus for transmitting data m a communications system, comprising means for channel coding the incoming data with a predetermined code; means for multiplexing and spreading the coded data stream; means for applying pilot tones; means for dynamically allocating sub-carriers m order to adapt the transmission performance according to the requirements of an individual user by using a relationship estimating the transmission performance taking account of the accuracy of the channel model to allocate the sub-camera.

According to another aspect of the present invention, there is provided a method of communicating using a multi-can-ier system comprising the steps of: i) estimating the transmission performance under consideration of the accuracy of the channel model, ii) allocating radio resources according to individual user's needs, iii) estimating the performance of different scheduling strategies in dependence of the number of users, adopting the scheduling strategy based on the result of step iii).

Further aspects and advantages of the invention are deemed in the appended claims, and features thereof will be apparent from the following

l O description.

Embodiments of the invention will now be described, by way of example only, with reference to the accompanying drawings, in which: Figure l is a block diagram illustrating a transmitter according to one embodiment of the present invention; Figure 2 is a diagram schematically illustrating Parallel Concatenated Convolutional Coding (Turbo Coding); Figure 3 is a diagram schematically illustrating iterative Turbo Decoding; Figure 4 is a schematic diagram illustrating the system and inputs for the dynamic sub-carrier allocation according to one embodiment of the present invention.

Figure 5 is a schematic diagram illustrating the time-frequency pilot pattern of a multi-carrier system; Figure 6 is a diagram illustrating the impact of channel delay spread on frequency correlation with respect to sub-carrier indices in a MC-SS system; Figure 7 is a schematic diagram illustrating clustered and symmetric pilot pattern of a MC-SS system according to one embodiment of the present invention; Figure 8 is a schematic diagram illustrating the dependence of the bit error rate for the distance from pilot tones for three different spreading factors.

Figure 9 is a block diagram showing schematically the elements of a communications system according to an embodiment of the invention; Figure 10 is a block diagram showing schematically the elements of a base station or Node B of the network of Figure 9; and Figure 11 is a corresponding block diagram showing schematically the structure of one of a plurality of terminals of that network.

Overview of embodiments Referring to Figure 9, a communication system such as a mobile telephony system comprises a plurality of user equipment (UK) such as mobile terminals 300a, 300b, in radio communication with a base station 100, provided within a cell, and having a fiend link connection to a backbone network (such as an IP network) via a switch computer 200. The 1P backbone network will not further be discussed since it is of conventional type.

The orthogonal frequency division multiple (OFDM) waveform used in the downlink communications comprises a plurality of subcarriers spaced apart along the frequency axis such that the peak of each subcarrier falls within the first null of its ncighbour.

Referring to Figure 10, the base station 100 comprises a receiver antenna 102 coupled to an uplink receiver 104 which receives and demodulates uplink signals from the terminals 300. The received signal from the receiver 104 is demultiplexed by a demultiplexer 110 into data signals from each user terminal (which are routed to the IP network computer 200) and uplink control signals, which are supplied to a control unit 120.

On the transmitter side, data signals intended for terminals 300 are received from the network computer 200 and passed to a multiplexer 116 where they are multiplexed, together with control signals from the control unit 120, onto selected OFDM subcarriers generated by an OFDM generator 115.

The OFDM signal is then amplified and transmitted by a downlink transmitter 114 coupled to a downlink antenna 1 12, for reception by the mobile terminals 300.

A carrier allocator 110, discussed in greater detail below, determines which subcarriers will be used to communicate with each mobile terminal 300, on the basis of the uplink feedback signals from the mobile terminals, and controls the multiplexer accordingly.

Conveniently, the uplink transmissions are also OFDMA, but it would be possible to use any other multiple access system such as CDMA, TDMA, or random access protocols such as ALOHA.

Referring to Figure 11, the structure of a terminal transceiver 300 of Figure 9 is shown. A downlink receiver antenna 312 receives the OFDM signal transmitted by the base station 100 and passes it to a downlink receiver 314 at which it is amplified and down converted and supplied to an OFDM demodulator 315. Selected channels from the OFDM demodulator 315, under control of a channel selector 310, pass to a demultiplexer 316 which separates out the control signals intended to control the uplink from data signals. The downlink data signals are then combined using, for example, maximum ratio combining (or any other suitable form of combination) and supplied for use, at a data port (for example connected to a display unit, or an analog to digital converter for audio reproduction). Pilot signals are routed to a control unit 320.

Output signals from the uplink feedback control unit are supplied to a multiplexer 306, together with uplink data (for example, user commands or voice data), and the multiplexed uplink signal is supplied to an uplink transmitter 304 for transmission via an uplink antenna 302 to the base station 1()0 (it will be appreciated that a separate uplink feedback channel could be provided, in which case the demultiplexer would be redundant).

It will be clear to the skilled person that, other than the modulation and RF components, the blocks making up the embodiment at the base station and the mobile terminals comprise suitably programmed digital signal processor devices (DSPs) or ASICs executing signal processing. Separate dedicated hardware devices may be used for the OFDM operations (specifically the Inverse Fast Fourier Transform or IFFT used in the transmitter components to map the subcarriers into a composite time- domain signal for RF modulation) and the Fast Fourier Transform or FFT used in the receiver components to map the time-domain signal back into component subcarriers).

In both the base station and the terminals, in order to receive data transmitted over the communications link, the received data are first demodulated, then processed in error control decoders using the redundancy to correct any errors occurred in transmission, such that the data are then available at the receiver's output port (for example for display or audio reproduction).

Figure l illustrates a block diagram of a transmitter 10 according to an embodiment of the present invention.

The binary data are encoded in channel coder 12, by coding the data bits, interleaving and mapping the coded data into constellation symbols.

The data stream is subsequently fed to a serial to parallel converter block 14 and is thereby multiplexed into Nparallel data streams, i.e. the N Spreading Bands, constituted of L subcarriers each.

In block 16 each data stream is spread over L subcarriers using spreading chip codes Cat to Cab., i.e. by duplicating the data stream L times and multiplying by the chip elements Cal to C' (one chosen spreading sequence) Specific Frequency mapping is applied in block l 8 and pilot tones (i.e. predetermined symbols known to the receiver and carrying no data) are introduced as will be described in more detail below. In block 20 an inverse Fast Fourier transformation is carried out and the data are fed into parallel to serial converter, wherein the data arc added and sent through the channel for transmission.

The operation of the system will now be described in overview.

Periodically (for example, every frame of a framed communication system) the base station l DO receives uplink feedback signals from the mobile to terminals 300. Each uplink feedback signal comprises data indicating the signal to noise ratio (SNR) experienced on that subcarrier.

Initially, when a session with a terminal is to be set up, the terminal signals to the base station to indicate its requirements - i.e. bandwidth and maximum bit error rate, or type of service required (which is implicitly associated with a bandwidth and bit error rate). The base station channel allocator then calculates a set of session parameters (including subcarrier allocations) for all the terminals it is in communication with, including the new one, so as to allocate channels to all terminals with in attempt to meet the requirements of all. The and is to allocate channels to each so as to match their bandwidth and quality requirements.

In the present embodiments, this is achieved by estimating, for each terminal, the average pairwise error probability produced by the decoder, and hence the average channel quahty, assuming as a starting point a candidate set of subcarrier frequency allocations, a predetermined pilot signal sequence, and uplink data indicating the current SNR experienced by each terminal on several pilot subcarriers that it is monitoring. When, for all terminals, the calculated quality of service matches the maximum allowed for the terminal, then the set of channel allocations is used; if not, then a different set of allocations is tested and so on until either an acceptable set of allocations is found, or no such set exists in which case the request for a new session is not accepted by the base station.

Whilst sessions are in progress, even if no new terminal requests a session, the base station channel allocator 110 attempts to reallocate channels based on new uplink SNR data, which may indicate that an existing allocation has become unsuitable for one or more terminals.

In order to transmit data over a communications link, data are digitally encoded, and are modulated from digital to analog and amplified for transmission over the communications link.

Turbo-Codine & De-codine An encoder for the Turbo encoding process (at the base station) is shown in Figure 2. This corresponds to the parallel concatenation of two 2() recursive systematic convolutional (RSC) encoders. These encoders are separated by one interleaving module fez. As these encoders are processing the same input bits stream x', this scheme is designated as parallel concatenated convolutional codes (PCCC).

Each RSC component (here chosen to be identical) is composed of two generator polynomial, namely feedback and feedforward polynomials, respectively g, (D) and g2 (D). Thus, two parity check sequences are generated, namely xP, and x2.

In order to efficiently vary the transmission rate, generally some puncturing can be processed on the parity check sequences.

The turbo-decoding process which takes places in the receivers at the base station and the terminals, performed by the decoder shown in Figure 3, is one of the most basic iterative scheme. Again two component decoders, called Soft Input Soft Output (SISO) decoders Do and D2, are serially concatenated via an interleaving process. The major key feature of this iterative process, is that the extrinsic information delivered by one SISO decoder, feeds the following SISO decoder as a priori information for decoding mfonnation bits.

The feedback loop iteratively improves the performance of this scheme.

First Embodiment: Turbo-Coded Multi-Carrier Suread-Spectrum Realistic Channel Estimates Systems When designing Channel Codes, a realistic estimate of their performance Is useful in order to evaluate the Coding for their future use.

As described above, in the paper by A. Ramesh, "Performance Analysis of Turbo Codes on Fading Chancels with Dvcrsity Combinmg", one first analysis has been carried out to provide performance evaluation for Turbo- Codcs used in the environment of MC-SS transmission systems, using the traditional Union upper bound framework. It is noted that in this analysis it is assumed that the weight factors involved in the diversity reception schemes are perfectly known. This hypothesis simplifies the analysis leading to optimal performance assessment. However, on the other hand, it is only a coarse approximation and does not allow to consider realistic estimates for system design parameters.

In the following, by way of contrast, there is provided a detailed, theoretical analysis of the sensitivity of Turbo-Codes performance in MCSS, including the effects of Maximal Ratio Combining (MRC) and Imperfect lO Channel Estimates.

In this way the upper bound performance can be estimated and used in design considerations of Turbo-Codes in such "degraded", and thus more realistic environments.

Traditional Union Bound Traditional Union upper bound for the Maximum Likelihood (ML) decoding of an (N,K) block code is given by: I) 'I.l(ti) 1() it., with A(cI) being the number of codewords with Hamming weight 1/, and P2(l) is the probability of incorrectly decoding to a codeword with weight it.

In S. Benedetto, and G. Montorsi, "Unveiling Turbo Codes: Some Results on Parallel Concatenated Coding Schemes", by IEEE Trans. On Info.

Theory, Vol.42, p.409-429. March 1996, and D. Divsalar, S. Dolinar, R.J.

McEliece, and F. Pollara, Transfer Function Bounds on the Perfonnance of Turbo Codes, TDA Progress Report 42-122, JPL, Caltech, August 1995, the authors propose an average upper bound averaged over all possible interleavers. Following their proposed framework, the average weight distribution is given by: Ll 'P(ll)) h airy where ( J!( a)' is the number of input words with Hamming weight i, and p(dli) is the probability that an input word with Hamming weight i produces a codeword with Hamming weight cl (which depends on the coding scheme (turbo coding or convolutional coding), the coding rate (i..e. / or 1/3) and the modulation level of the trellis modulation (i.e. 64QAM) So, we get the average upper bound: I',,, i(l)*l>.l) . tf,,, " i;t. ) J(lIl) If (f) {I adult

K

z J. 1 [/>(CI3] and for the bit error probability: | hi [( 1'1 (1) Equation (1) is known as the Divsalar equation.

It provides for calculation of the error probability (the BER and hence Quality of Service) given the pairwise error probability.

The key point in this embodiment is therefore to evaluate the pairwise probability of error in the context of a combining diversity scheme. In the following, the maximal ratio combination will be considered.

General Diversity Framework 1 et us note the output SNR from the receiving device: Z(()2 (2) n = , lo.

=- t,/i 72'----'' I then conditioned to the channel facings (sub-carriers) , we get: /', (am) - (am,- 1) (jl:,l 1 5 rt-1 as.' _ lye is, A, are i.i.d, we can note (lard Ji|)t I; | n f't;; i) it; (3) I, r., i n I; n I With Craig's formula t)()=- sexy i fJ6' We finally get 1>' (J) - In l | J'i (In) AND{ 5,ln 2) An (f) | 7,. (I) L, 2 - nJ A,, t {J() r If we note ' = Ipr-;,)., ].mn-o.7' then the resulting SNR distribution will impact the average pairvvise error probability.

Turbo-Codina Upper Bound, with MRC and Imperfect Channel l 0 F,stimate We will now introduce the Imperfect Channel Estimate by means of correlation factors between the pilot channel estimates and the true channel values.

The starting point is thus the following double integral: i: (hi)- Jl^r (it) tlY 'l{) (4) * < 1) We just have to focus on the derivation of this first integral: it = I/..(,l) e,5'n' off/ (., Based on the work by M.J. Gans, "The Effect of Gaussian Error in Maximal Ratio Combiners", IEEE Trans. On Comm. Tech., vol coin-19, N4, August 1971, the SNR distribution w ith Imperfect Channel Estimation is given by the following relation: Pr (Y) = A(k. A) (k i)! r, (5) vvhcrebydefnition (k,P)=(k-) (I-p) p) and p is the correlation factor between the true and estimated channel weight. A(k, p) = B' c-' (p2) Note that are the Bernstein Polynomials So, we get 1=A(k,p)-- y ex p -y -+ dy (6) =' r(k) Ink {o7 [ (r 2 sin )] } I S Now, we note for simplicity zi= IY eXP|-Y (l:+2 sin7 (J)] dy and Q = - + 1 2 sins t9 +.

then by using the Gamma Euler function dcfitlitio',: ()= |l'-' e' At F(k) We obtain straightforwardly Q So by using this and equation (G), we now have: I'=>,A(k,p) (r Q)'

JO

I sin c9 = Q sin t) + with and finally I'=(k,P) r k=! Lsin,0+] J' Thus, by using equation (3), That leads to the following relation: PI ()= Jz ( P)[sinr+r] [ 2] By noting, we simplify this expression Indeed, consider the following notation: X(k P)= 4(k, p) Lsint8+ F] We thus have to focus on the new relation: (at) For sake ofsimplicity,we note X(k,P) Ark' This second integral is the expression of multnomial sencs, meaning that we can write 1, in the followin,: I (\ ) i \t d! ) ,. ..

i'+;: + +;l =/ with,; Il*',=nts,in20r/l n[.4(k,p)l'' i=1 I I Lsln B+ l2] /=l then first compute, sin2R 1 sings, alp' ) H'Lsn'd+/21 =Lsin29+21 also we get (L-1)'; )( }; 2(-;, for sake of clarity we note v(i,,i,,...,i/.L.d.P)=i!, ! i! n['4(k'P)] = lo at) (I p2(/ i>. p Finally, this second integral can be written as: . Ad, 1, = 7, (il. i, ,.... i/, L'd, p) I n r at 1. 1l Sins 0+ _ +, + +,,= 2 By using this equation and equation (7), we obtain: +/ I,(L'd, {))=- (1, trio o Y/(l''' iL'Ll P) I if sin] I'': + +'L=' 2 And as Alouini uses the following integral family: Jn'(C)='T![Sin20tC] where parameters are given by r C-2 m = Ad, k in k=l As m is an integer, we can furthermore write: J,n (c) [P(c)] ( k) [I r(c)] ith P(c) = 2 [I - a] As a conclusion, the new average pairwise error probability, with MRC and imperfect channel estimate is given by: P24'RC (Led, p) = -- (i, . , .., i, ) (Zk;, )( 2) Thus, Tic have a new, more accurate measure of the pairwise error probatnhty, which can he inserted into Equation (1) above to yield the BER.

The equation takes as inputs the average SNR reported by the terminal for the subcarriers, and the index of the subcarrier (which reflects how far away the subcarrier is in frequency from the pilot tone). It is a function of L, the length of the spreading sequence (i.e. the number of subncan-iers over which the signal to the terminal has been spread), it! (which is the Hamming distance between codewords, a function of the code and level of modulation used) and p, the estimated error due to the subcarrier being spaced from the pilot.

From equation (8), it follows that the ideal case, i.e. with perfect channel estimate (p = 1)is given by: P2*C(L,d'P=I)=JLd(-) Geometric Interpretation of the Pairwise Error Probabilitv We w ill demonstrate in this part, that based on the expression of Eq(8), the Pairwise Error probability with Hamming distance d of Turbo Coded transmission systems with L diversity MRC reception, and imperfect channel estimate is actually the barycentre of a mesh network whose point controls are the pairuise error probability with Hamming distance varying from 0 to d and MRC reception with varying diversiy from 1 to L, when the channel is perfectly known.

As described above, the weighting factor from Eq (8) was given by: (il,i2,....iL, L l P)= j!i! i! n [(k P)] !. ! iL! n(k _ | (I -r-)N); P ln orler to demonstrate the Yeometric theorem, we need to estimate the globalsummation of the above function with respect to all indices: (i,,i,,...,i/,L, ti, p) 11 1. lL ii i!i! i! 4(k-1) ( P P d! L L( L I)I, ); ) ] 11 /, 11 il.i2...i/.. i=1 -1 i,!il! iL! nl[(k-l) ] and now with A(k,p)=( ) (I_p2) .p_(k-), and A(k,p) =Bi, l(P-), --(il,i',---,iL, L,. p) 1' 1. 1, = j!i! i! ti[(kp)] L 1'=J = [E A(k P)] Bt due to the Bcrnstcin polynomial property: A(k, p) = I =' Indce(i A(k P)=(L i) (Ibex)'-' xk-' with x=p' I=1 k=1 so by noting A=k- 1, and N=L- I, this gives A(k, A)= ( (1 -x) XK = [(I -x)+x] =1 =1 K=0 Finally we get the following remarkable property: | (il,i', ,iL,L.d.p)= 1| (9) Application to Time-Frequencv Pilot Pattern In order to illustrate the applicability of the estimate described above, an expression for the correlation factor p is derived as an example.

Fig. 5 illustrates a Time-Frequency Pilot Pattem, as is usually considered in multi-carrier based Systems.

In a first step, factors are analysed along each dimension, and subsequently, the 2D (time and frequency) correlation factor is derived.

IS Frequencv Correlation For an exponential decaying power delay prosaic, we can express the frequency correlation as: P(J)= Al +(:r Of r,<,.) where p(AJ) is the frequency separation between the pilot sub-carrier and the data sub-carrier, and rRS represents the Channel Delay Spread As the transmission system is MC based, we can note: Of = I = [V = f, ,.h. To. N,,,h, N.,, the constant frequency width of sub-carriers.

Then introducing this parameter we get: Pi = P(k Alum)= I 41 + (27 k f,,,he rK\\ ) where k is the sub-carrier index.

Time Correlation In the same manner we can get the time correlation relation: (TV) = Jo (by do At) u here At is the time separation between the pilot symbols and the data ones.

By introducing OFDM based parameters such as T = 1 fubc Ti = TU + To = (Nit, + Ng) To we can cypress the time correlation w ith the nth OFDM symbol p,, p(l7 Tt) I'm (lVIl, + ELF) TO | JO( n (hi fl, + Ng) J) Figure 6 is a diagram illustration of the impact of the channel delay spread on the frequency correlation with respect to the sub-carrier index. Too examples are illustrated for a delay spread of 50 and 150 ns respectively. s

Time-Frequencv Correlation For the Time-Frequency case, we just need to combine both results about the correlation to get the expression of the 2D correlation factor: P(At,Af)= p(Al) p(k ^f,,hc)= 41 + (24 f,,,h, rm,S) (12) That means that by varying a single parameter (i.e. the spreading factor) the transmission performance can be varied or adapted to the user's requirements.

Dvnamic Sub-carrier Allocation Referring now to Fig. 4, one system for dynamically allocating sub can-iers in a multi-carrier systcn1 is described.

The received traffic and uplink data from different terminals 00 on the data uplinl;, and front the network 200 for difEcrent terminals 3000n the downlink, are supplied to the channel allocator 110, which is used forjointly 20optimising the DLC and physical layer. It conprises blocl; 122 for applying the scheduling policy of the system (for example, to favour certain classes of users such as emergency or premium rate users, as discussed in "Scheduling Mechanisms for Rate Adaptive Multi-Carrier Spread-Spectrum (MC-SS) Transmission Systems" by Thierry Lestable, the present inventor, presented in WWRFI I Meeting 10 June 2004) and block 124 for performing the dynamic sub-carrier allocation. In block 124, the relation of equation (8) described above is used to manage the radio resources.

Input values and parameters used for the sub-carrier allocation (and, if necessary, any scheduling policy) are: the measured Doppler frequency error f D, the measured channel delay spread TRMs, the average signal-to-noise ratio (SNR) for each terminal (based on measurements taken at the terminal and transmitted on the uplink signalling channel), the channel coding parameters of the modulation and coding scheme proposed to be used for each terminal (specifically, the probability p(dli) that an input word with Hamming weight I produces a codeword with Hamming weight d), the spreading factor length SF proposed to be used for each terminal (i. e. how many subcarricrs are used - or, put differently, over how many subcanrier clusters the signal is spread), and the requested target hit error rate for each terminal (BER target), defining the required quality of service.

In this embodiment, the pilot pattern is symmetric with clustering of subcanriers around each pilot, as is frequently used in OFDMA schemes. Such a pattern is illustrated in Figure 7. In this way the total bandwidth is sub divided in clusters whose number depends on the length I, of the Spreading Factor (SF). One subcanier within each cluster is allocated to each terminal; occupying the same subcanrier position (i.e. index along the frequency scale) within each cluster, for the chip codes (i.e. the spreading codes).

In this case, we can now apply the theoretical derivation of the tight bound on turbo-coded transmission of each user by using equation (8) and equation (l), with both varying spreading factor and subcarrier position in order to derive the dynamic subcarrier allocation.

In other words, taking the measurements and the required quality of service as inputs, the following steps are perforated: a candidate subcanrier allocation is made by the base station; the BER is calculated for each terminal on the basis of the candidate allocation; if the BER for all tenninals is below the target BER for each, then the candidate allocation is adopted; if not then a new candidate allocation is made by the base station, and the process is repeated; if no suitable allocation can be found, then a constraint is relaxed (for example, the maximum allowed BER is reduced, or the spreading factors are increased, or the coding rates are reduced, or the number of terminals is reduced by dropping one session).and the process is repeated.

Once the dynamic subcarrier allocation has been derived, it can be used to test scheduling policies to select one of a plurality of predetermined scheduling policies. Again, such a procedure has been described in the PhD thesis and the article "Scheduling Mechanisms for Rate Adaptive Multi Carrier Spread-Spectnm (MC-SS) Transmission Systems" by the present inventor T. Lestable, cited above. Alternatively, new, improved scheduling policies can be derived, and the testing and derivation of scheduling policies can be carried out in the same way.

It is noted that in a different context, a previous derivation process has been proposed by the present inventor in T. Lestable "Design of Link Adaptation Mechanisms for Future Generation Multi-Carrier Spread Spectrum (MC-SS) Systems", PhD Thesis (in French), October 2003, Orsay University, Supelec, Paris, France, for MC-SS systems with optimal power and rate kink adaptation (OPRA), where the QoS is based on capacity (i.e. the throughput) rather than the BER.

Second Embodiment: Convolutional Codina of MC-SS Systems Whilst in the above described embodiment Turbo-Codes have been described, it is appreciated that alternatively other coding schemes may be used.

The same principles can be applied to other forms of error correcting encoding, as will be illustrated by the following embodiment.

According to John G. Proakis, Digital Communications, 3'6 edition, McGrawHill International Editions, chapter 8-2-3, (pp. 486-488), the following relation gives the Bit Error Probability for any convolutional code, depending both on its transfer function, and on the pairwisc error probability: +r Ph < , find P2 (d) ( 13) d =d hat whereby P:(d) is the pairwise error probability, and,B,, = ad f (d), with a, =""number of paths of distance d from all zero path that merge with the all-zero path for the first time".

These parameters are directly related to the trellis structure of the code itself, and to the transfer function: +a) T(D' N) = it, ad D N d=d/r Thus, equation (l 3) can be directly applied to convolutional coding, as our key function involving reception diversity (MRC) and correlation coefficient p is the pairwise error probability P2(d).

Then, the resulting BER is given by equation (13) for the MC-SS System using Convolutional Codmg, and by equation (8) for Turbo-coding.

Using equation (13) instead of equation (8), a strategy lor adapting pilot pattern or jointly adapting pilot pattern and spreading factors can be derived in the same manner as explicitly shown above for the case of the turbo codes.

This invention may be used together with a method of uplinking channel quality data as described in our co-pending UK application GB04 (agent's reference J00046532GB, filed on the same day as the present application), and/or with a method of pilot signal adaptation described in our copending UK application GB04 (agent's reference J00046533GB, filed on the same day as the present application), both of which are incorporated herein in their entirety.

It is to be understood that the embodiments described above are preferred embodiments only. Namely, various features may be omitted, modified or substituted by equivalents without departing from the scope of the present invention. The present invention extends to any and all such variants, and to any novel subject matter or combination thereof disclosed in the foregoing.

Claims (17)

1. Claims 1. A method of communication, wherein multiple data streams are

   transmitted simultaneously and channel coded are used which are coded using a predetermined code, wherein radio resources are allocated according to an individual user's traffic requirement by dynamically allocating sub-carriers, using a relationship for estimating the transmission performance taking account of the accuracy of the channel model to allocate the sub-carriers.
2. 2. A method according to claim 1, wherein multi-carrier spread spectrum transmission with channel coding is used.
3. 3. A method according to any preceding claim, wherein said predetermined code is turbo-coding.
4. 4. A method according to any of claims I to 2, wherein said predetermined code is convolutional coding. 2()
5. 5. A method according to any preceding claim, wherein the transmission performance is specilicd by a magnum bit error rate.
6. 6. A method according to any preceding claim, wherein said relationship for estimating the transmission performance takes into account maximal ratio combination.
7. 7. A method according to any preceding claim, wherein said relationship for estimating the transmission performance takes into account imperfect channel estimates.
8. 8. A method according to claim 7, wherein the imperfect channel l O estimate is introduced by a correlation factor describing the correlation between the pilot channel estimates and the true channel values.
9. 9. A method according to any preceding claim, wherein said relationship for estimating the transmission performance includes the average pair wise error probability.
10. 10. A method according to any preceding claim' wherein frequency spreading is used.
11. 11. A method according to claim 10, wherein radio resources are allocating by jointly allocating the sub-carrcrs and the spreading factor ol the frequency spreading.
12. 12. A method of communication, wherem multiple data streams are transmitted simultaneously and channel coded are used which are coded using a predetermined code, and frequency spreading is applied, wherein radio resources are allocated according to an individual user's traffic requirement by dynamically allocating sub-carriers and a spreading factor of the frequency spreading, using a relationship for estimating the transmission performance taking account of the accuracy of the channel model and the spreading factor to allocate the sub-carriers.
13. 13. A transmitter apparatus for transmitting data in a communications system, comprising means for channel coding the incoming data with a predetermined code; means for multiplexing and spreading the coded data stream; means for applying pilot tones; means for dynamically allocating sub-carriers in order to adapt the transmission performance according to the requirements of an individual user by using a relationship estimating the transmission performance taking 2() account of the accuracy o' the channel model to allocate the sub- carriers.
14. 14. A transmitter system for use In a communications system, adapted to nnplemcnt the method set out m any of claims 1 to 12.
15. 15. A method according to any preceding claim, further comprising the step of comparing different scheduling policies.
16. 16. A method according to any preceding claim, further comprising the step of selecting a particular scheduling policy in dependence on the dynamic subcarrier allocation.
17. 17. A method of communicating using a multi-carrier system comprising the steps of: i) estimating the transmission performance under consideration of the accuracy of the channel model, ii) allocating radio resources according to individual user's needs, iii) estimating the performance of different scheduling strategies in dependence of the number of users, adopting the scheduling strategy based on the result of step iii).