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A hybrid multiple access scheme:OFDMA-IDMA
Hongxia Bie, Zhisong Bie
Abstract-In this paper, we propose a hybrid
multiple-accessscheme which combines IDMA (Interleave division
multipleaccess) and OFDMA (Orthogonal frequency division
multipleaccess), named by OFDMA-IDMA. The advantages of this
schemeare analyzed and the probable application scenarios
arediscussed. A scheduling method for uplink based on
convergenceanalysis techniques is also proposed to group users to
share thesame time-frequency resources effectively.
Index Terms-Interleave-division multiple access(IDMA);Orthogonal
frequency division multiple access(OFDMA);Convergence analysis; SNR
evolution
I. INTRODUCTIONDMA is the dominant multiple access scheme in the
thirdgeneration mobile communication systems. However, the
nature of interference-limited decides that the capacity ofCDMA
system with conventional receiver can not be improvedfurther.
Orthogonal multiple access schemes (e.g. OFDMA,SC-FDMA) have the
advantage of without intra-cell MAI andhave been considered
promising multiple access schemes forthe mobile systems in the near
future. But as was shown [1],only wave-division-multiple-access
schemes can approach anypoint in the capacity region of
multiple-access-channel (MAC).Multi-user detection (MUD) is a key
to improve the spectrumefficiency of wave-division-multiple-access
schemes, but theconventional MUD techniques designed for CDMA
arecomputational complexity intensive because of the
correlationamong the signature sequences of the users and the
asynchrony.In [2], Li Ping etc. proposed a kind of non-orthogonal
multipleaccess schemes named by IDMA, which can be considered as
anew kind of wave-division multiple access technique. Due tothe
introduction of chip level interleaver, joint detection can
besimplified by using Gaussian approximation. Their discussionwas
limited in the low rate channel coding environments andtheir aim
was to use IDMA as an independent spectrum spreadmultiple access
scheme to replace CDMA. They also gave asemi-analytical performance
analysis for IDMA and proposeda power allocation technique for
performance optimization [3].
Hongxia Bie is an associate professor of the School of
InformationEngineering, Beijing University of Posts and
Telecommunications, Beijing,P.R. China. (e-mail: biehx@
bupt.edu.cn).
Zhisong Bie is a Ph.D candidate of the School of Information
Engineering,Beijing University of Posts and Telecommunications,
Beijing, P.R. China..(e-mail:zhisongbie(gmail.com).
II. SYSTEM MODELWe adopt OFDMA as the representative of
orthogonal
multiple access schemes. The minimal scheduled units namedby
chunks are time-frequency blocks which consist of a certainnumber
of subcarriers. A chunk must be allocated to only oneuser
exclusively for OFDMA. By so-called OFDMA-IDMA,we mean that the
same chunks are assigned to more than oneuser, each of which has
its own user-specific interleaver. Thechannel coding scheme of each
user can be either same ordifferent.
The source bits sequence of kth user {bk } is coded by acoding
function ok(bk) and then is interleaved to {kk } byinterleaver ITk
. This sequence is modulated to sequence {Xk j}and then is mapped
to the allocated chunks.
The total number of subcarriers of OFDMA is denoted byNC. P
denotes the set of subcarriers which are assigned to thetarget
users. The sampled sequence with cyclic prefix for theuser indexed
by k can be expressed by
1 Nc-s NE-I X ej2;TnvIN, v=-L I... ...N -1 (1)v,k,j AT nk,C v
L,..., c
1Ncn=O,nczPWhere Lg denotes the number of samples of cyclic
prefix
and x k j is the modulated data of thejth OFDM symbol of thekth
user which is mapped to the nth subcarrier. After the CP isremoved
and FFT is implemented, the received signal afterde-mapping can be
expressed by
yj (n) = E k (n)xk,j (n)+ vj (n) (2)k=1
where Hk,j (n) is the flat fading factor of the nth subcarrierof
the kth user (quasi-static channel is assumed) and v (n)represents
the complex Gaussian noise of the nth subcarrier.Because the coded
block often occupies several OFDMsymbols, by some abuse of
notation, we rewrite the receivedsignal corresponding to thejth
symbol of coded block as
K
Y (j) = Hkjjxk ( j + Vi (3)where j is the index to the position
of the coded symbol in thecoded block, which is very similar to
that ofIDMA, except thatH, j is the frequency domain factor of the
correspondingsubcarrier, rather the time domain fading factor. In
order to
1-4244-0463-0/06/$20.00 2006 IEEE
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simplify the derivation of algorithms, QPSK constellation
isassumed, so yi (n), HkIj (n), vj (n) e g and transmittedsignal
Xk,j(n)eAk Q Ak ={1+i,-I+i,1-i,-1-i}.
III. JOINT DETECTION ALGORITHMBy comparing (3) with the equation
(2) of [2], the onlydifference is that the frequency fading factors
H k are notconstants during the coded block because the channels
arefrequency selective. We adopt the low complexity ESE(elemental
signal estimator) algorithm derived in [2]. Thisalgorithm is
derived through Gaussian approximation based onthe assumption that
the interfering symbols are independent ofeach other. This
assumption is reasonable when the codedblock is long enough because
of the user-specific randominterleavers.We reformulate the
algorithm for QPSK signaling as following.The received complex
signal can be expressed by:
y(j) E (HRe.XRe (j) Imxx Ij)k
+E (Hk (j) + Hk Xkj(k )) + Vjk (4)
Re (j) i)In order to detect Xk ()and kXU separately, we have
H y(j) = IH x Re (j) HiIj)H2 H (j)In the following part, we
focus on the detection ofXk
Equations (6)-(12) give the algorithmRe(H (j)) HyYR (j) + H'my'm
(j) |H j12 R (j)(YRe (j)) e(HE (XkRe(j) HmE (xm (j)))
k
D(y (j)) = (HR ) D (x (j)) +(H ) D (x (j)) +k
T(j) HReHm(D (XRe(j)) D (xm (j)))k
E ( Re (H ; )))=H E ( Y (jy) ) + HImE (Y( ))k,j 12E(XR (j))
D (Re (Hkj ~;(j) = (HRe) DH(yw (j))( k,j)D (yk(J)) k,j|lHk,j (XR
(j ))
L x(j)R) = 2 (H ))e (HjY () - E (Re (H ; (j)))D (Re (Hk jSk
(j)))
(5)Re
k (J)
The T in (9) is the covariance of Y () and Y (i),which is
introduced for computational cost saving because it isshared by all
users. E() denotes the expectation and D )
LLR xj)denotes the variance. Similarly, we can get the ( ())In
the process of iterative joint multi-user decoding, the
expectation and variance of xk (j) can be calculated by usingthe
previous output extrinsic LLR of SISO(Soft-in soft-out)decoder.
There are a series of SISO decoding algorithms fordifferent coding
schemes. We will not discuss the SISOdecoder in detail in this
paper.If the coding schemes are combined properly, after
severaltimes iteration between ESE detector and SISO
decoder,desired performance can be reached.
IV. CONVERGENCE ANALYSIS AND USER-GROUPINGMETHOD
Density evolution (DE), EXIT chart, and SNR evolutiontechniques
were used to analyze the iterative receiver. Thesetechniques can
also be used to analyze the convergence ofOFDMA-IDMA receiver.
Let's take SNR evolution as anexample to demonstrate the
user-grouping method.The SNR evolution analysis can be expressed by
[4]
SNRk Hk 22k new H 12f(SN old)+k'#k
(13)
whereHk is assumed to be constant over the total resource(6)
block and SNR and SNRkld represent SNR value after(7) and before
one iteration, respectively, and a2 is the variance
of the complex Gaussian noise. fk (C) is a characteristic(8)
function of certain SISO decoding algorithm for a special
coding scheme, which can be easily obtained by Monte
Carlosimulation. f, (SNR ) of two kinds of convolutional code
f(SNR)
(10)
Z 0.5(0)0.4-
(1 1)
(12 SSNR (dB)(12) Fig.l. The f(.) function of (2,1,5)
convolutional code and (3,1,9)convolutional code(BCJR decoder)
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with BCJR decoder are shown in Fig. 2.
Provided all the channel response H, and the variance of
noise2
5 is perfect known, we can easily estimate the SNRperformance
after several iterations for every user byimplementing (13)
repeatedly, and then the BER(bit errorrate)performance can be
estimate according to anothercharacteristic function BER =
g(SNR).SNR evolution technique is used to derive optimal
powerallocation scheme in [3]. In this paper, we propose an idea
tocombine this technique with resource scheduling toaccommodate
more users and improve spectrum efficiency.The SNR evolution
technique can be used to judge whether theusers can share the same
chunk. The detail description of theidea is as following.1)
Estimate channel quality informationBefore scheduling, channel
information, including frequencydomain response and Gaussian noise
variance must beestimated accurately. For OFDMA-IDMA,
channelinformation can be easily gotten by using pilot symbols
intime-frequency grids.2) Choose proper coding scheme for each
userAccording to the channel condition and the
performancerequirements of each user, proper coding scheme can
bechosen. Their channel coding schemes can be different.
Codingscheme selection can also be combined with
resourcescheduling.3) Specify the iteration timesIn this scheme,
the iteration times can be predetermined,denoted by ni4) Find the
characteristic functionsThis function f (SNRJ has no closed form
expression and isobtained by Monte Carlo simulation. A series
look-up-tablescan be set up in scheduler. According to the chosen
codingscheme and the required BER performance, the target SNR canbe
obtained by using the function k (SNR) , denoted bySNRk obj
5) Try to group user, allocate resource, and implant
SNRevolutionAccording to some criteria, try to group users and
allocateresources, and then SNR evolution based on equation (13)
isimplemented for ni times for each group. After the final
SNR_f,literation, we get6) Judge whether the combination is
validIf for all the users, k_final 2 SNRkobj holds, then the
combination is valid, otherwise, continue to judge
anothercombination.By using this method, more than one user can
share the samechunks and their performances are ensured.
V. SIMULATION RESULTIn this part, a simple example of OFDMA-IDMA
is given. Inthis example, we assume that two users share the
sametime-frequency block. The two users use (2,1,5) and
(3,1,9)convolutional code, respectively. The ratio IH I'IH,I' is
set to be
10
1010
LU 10 -m
10-4-H- (3,1 ,9) mutiluser
1 o--E>- (3,1,9) single-E- (2,1 ,5) multiuser--G
(2,1,5)single
10 0 1 2 3 4 5Eb/NO (dB)
Fig.2. Performance of OFDMA-IDMA
2.239 and 1H is set to be 1. 10 times iteration is
implementedbefore decision. Static channel is assumed. Fig. 2 gives
thecurves of BER performance of each user versus thecorresponding
Eb/NO. The dashed lines show the single userdecoder performances
for comparison.It can be seen clearly that if properly designed by
integratingIDMA into OFDMA framework, spectrum efficiency will
beimproved without degrade the performance of each user.
VI. CONCLUSION AND COMMENTSOFDMA-IDMA is a new kind of hybrid
multiple accessscheme. It can get higher spectrum efficiency under
somechannel condition. There must be a scheduler to judge
whetherthe users can share the same time-frequency resources.
Ascheduler combined with SNR evolution technique can meetthis
requirement. The concrete scheduling algorithms should bedeveloped
to support the hybrid multiple access scheme.It is apparently that
OFDMA-IDMA has some advantages overpure OFDMA and pure IDMA.
Compared with OFDMA,OFDMA-IDMA can bring higher spectrum efficiency
undersome condition. Especially when the size minimum scheduledunit
is not small enough, OFDMA-IDMA can bring someadditional scheduling
flexibility and can accommodate moreusers. Compared with pure IDMA,
by using the framework ofOFDMA, channel estimation can be easily
implemented.Computational costs can also be reduced because no
Rakereceiver needed to fight against multi-path effect.
REFERENCES[1] R. Gallager "A perspective on multiaccess
channels". IEEE
Trans.Info.Theory, Vol.3 1 No.2, pp. 1772-1793, March 1985[2] Li
Ping, Lihai Liu, K. Y. Wu and W. K. Leung, "On
interleave-division
multiple-access," IEEE Intern. Conf. on Commun., ICC'04,
pp.2869-2873, 2004
[3] Li Ping and Lihai Liu, "Analysis and design of IDMA systems
based onSNR evolution and power allocation," Proc. VTC'2004-Fall,
Sept. 2004
