scma: a survey on advancement towards 5g...

SCMA: A Survey on Advancement towards 5G

Communications

Madhura Kulkarni1 and Dr. Rajeshree Raut2

1 St.Vincent Pallotti College of Engineering & Technology,

Nagpur, -441108, {[email protected]} 2 Shri Ramdeobaba College of Engineering & Management,

Nagpur, {[email protected]}

Abstract. The requirement to connect large number of users efficiently led to

the refinement in wireless communication from second generation to fifth

generation. The enhancement of cellular communication system involves use of

various multiple accesses. This article aims at elaborating the multiple access

techniques progressing from 2G -5G and describes SCMA Sparse Code

Multiple Access one of the NOMA (Non-Orthogonal Multiple Access)

techniques used in 5G cellular communication system. It is a codebook based

multi-dimensional non-orthogonal spreading technique. It involves combining

of QAM mapper and spreading signature blocks into a single block of a SCMA

spreading encoder having SCMA codebook set that results in a multi-

dimensional codeword. This paper describes the basic design of the encoder and

decoder along with the concept of codeword used in it. It also explains the link

implementation for the SCMA for its application.

Keywords: SCMA; LDS; non-orthogonal multiple-access; multi-dimensional

constellation; 5G; LTE.

1 Introduction

The 5G wireless communication involves diverse applications, which will be

deployed by 2020. The most important requirement of 5G is its high spectral

efficiency. Apart from that high throughput, better service, quality, low control

signaling and lower latency are some of the requirements to be met while using any

access. In a cellular system the channel bandwidth is limited whereas, it has to

accommodate maximum users in it, thus multiple access is a technique that helps the

cellular communication to be more economical by maximum utilization of channel

bandwidth as a physical layer technology. It enables the wireless base stations to

identify various users and serve them.

The different ways that allowed access to the channel included mainly orthogonal

and Non-orthogonal access. In orthogonal access the cross correlation of signals from

different users is zero [1], which can be achieved by Frequency Division Multiple-

Access (FDMA), Time Division Multiple-Access (TDMA),Code Division Multiple-

Access (CDMA), Orthogonal Frequency Division Multiple Access(OFDMA) Non-

orthogonal schemes allow non-zero cross correlation among the signals from different

Advanced Science and Technology Letters Vol.147 (SMART DSC-2017), pp.487-498

http://dx.doi.org/10.14257/astl.2017.147.68

ISSN: 2287-1233 ASTL Copyright © 2017 SERSC

users [1], such as in random waveform Code-Division Multiple-Access (CDMA) [2],

Trellis-Coded Multiple-Access (TCMA) [3] and Interleave Division Multiple-Access

(IDMA) [4]. Power Domain Multiple Access, Low Density signature OFDM

(LDMA), Pattern Division Multiple Access (PDMA), Building block sparse

constellation based Multiple Access (BOMA), Sparse Code Multiple Access (SCMA)

and Lattice Partition Multiple Access (LPMA) [7] and many more. The multiple

accesses used in communication from 2G-5G is shown in Fig.1

�

Fig. 1. Multiple access Techniques used in the communication system

The 2G communication system made use of basic multiple access that is, TDMA

and FDMA wherein the users are scheduled on orthogonal time slots.TDMA is a

multiple access method which allows different users to use the same channel

bandwidth by dividing the transmitted signals from the users into the different time

slots.

Fig. 2. TDMA where channel bandwidth is orthogonal to time in time-frequency and code

domain [11]

Advanced Science and Technology Letters Vol.147 (SMART DSC-2017)

488 Copyright © 2017 SERSC

FDMA is a multiple access method in which the channel bandwidth is divided

completely according to the number of users. Thus, the complete channel bandwidth

is utilized by the user for the specific time period.

Fig. 3. FDMA where channel bandwidth is orthogonal to frequency in time-frequency and code

domain [11]

The 3G communication system later made use of CDMA where the channels are

non -orthogonal in frequency and time domain but orthogonal in code domain. Code-

division multiple access (CDMA) is a multiple access method where different

transmitters can send the signals simultaneously over the same channel bandwidth

Fig. 4. CDMA where codes are orthogonal to frequency & time in time-frequency and code

domain [11]

The 4G communication systems, widely known as Long Term Evolution (LTE)

makes use of OFDMA, where the users are orthogonal in 2D frequency-time domain.

Orthogonal resources are occupied by the users for communication. Being the access

with single user detection it becomes comparatively easy for implementation. Here

the subsets of sub-carriers are assigned to the individual user. It is derived from

OFDM, that is Orthogonal frequency division Multiplexing that aims at allocating the

users in time domain only, where as OFDMA aims at allocating the users in both time

and frequency domain as shown in the Fig.5.1 and Fig 5.2 respectively.


Copyright © 2017 SERSC 489

Fig. 5.1. OFDM Fig. 5.2. OFDMA

As a result of limited users of orthogonal resources, which is proportional to the

number of users, 5G communication system has led to the extensive research on

various multiple accesses, that can meet the three basic demands as per 3G

Partnership Project (3GPP) [5][6], which includes massive Machine type

Communication (mMTC) [5][6], Ultra reliable & Low Latency communication and

enhanced vehicle-to-everything (eV2X) communications [5][6]. To achieve the same,

5G communication systems require large connectivity with good throughput and

spectral efficiency [7]. These challenges can be addressed by introducing NOMA

techniques.

The Table.1 shows the comparison of frequently used schemes in NOMA [7] with

their multiplexing advantages and disadvantages. In a communication system various

channel properties of the communication link are referred to as Channel State

Information (CSI), which is one of the important parameters responsible for the

quality of wireless communication systems. If CSI is not estimated properly, cross

layer interference limits the potential performance gain of MU-MIMO [8]. If we

compare various NOMA techniques listed in the Table.1 we can conclude that LDS-

CDMA, LDS-OFDMA and SCMA are the techniques where CSI is of least

importance, hence are more desirable. In this paper we will be focusing more towards

the study of SCMA.

Table 1. Comparison of various Access Techniques in NOMA [7]

Schemes Characteristics Advantages Disadvantages

Power-Domain

NOMA

Power Domain

Multiplexing

High SE, Compatible to

other techniques

Need user pairing Error

propagation in SIC

LDS-CDMA Sparse spreading

CDMA

No Need of CSI, Near

optimal MPA detector

Redundancy from

coding

SCMA Sparse spreading

Multidimensional

constellation

No Need of CSI, Near

optimal MPA detector,

More diversity than simple

LDS

Redundancy from

coding,

Difficult to design

optimal code book

LDS-OFDM Sparse spreading

OFDM

No Need of CSI,

Near optimal MPA

detector, More

fit for wide-band than

LDS-CDMA

Redundancy from

coding



PDMA Sparse spreading

Multiplexing in

power code and

spatial domain

More Diversity, Near

optimal MPA detector,

low complexity receiver

Redundancy from

coding,

Difficult to design

optimal patterns

BOMA Tiled Building block Simple structure

compatible to current

system low

complexity receiver

Need user pairing Not

very flexible.

LPMA Multilevel lattice

code Multiplexing in

power and code

domains

No Need of user clustering Specific Channel

Coding

2 Need for SCMA

SCMA does not require the CSI for the transmitter and the receiver in the

communication link. It is also responsible for reducing the interference in MU-MIMO

to enhance the link performance [8]. It enables grant free transmission with low

overhead & low latency for sporadic small packet transmission [8]. The QAM

modulation and the LDS spreading are replaced by multi-dimensional codebooks in

SCMA [10]. Despite of large number of users the collisions are less and have better

coverage because of the spreading gain. The Table.2 gives the comparison of main

aspects of LDS and SCMA which makes use of Message Passing Algorithm (MPA)

[11]detector at the receiver with same structure and complexity over the codewords

and symbols.

Table 2. SCMA Vs LDS [9]

Schemes SCMA LDS

Multiple

access

yes Codebook Domain yes Signature Domain

Sparse yes Sparse codewords yes Low Density

Signatures

Coding Gain yes Data carried over

multi-dimensional

complex

codewords

No Data carried over

QAM symbols

Degree of

Freedom

J codebooks each with

M codewords

J Signatures

Receiver Codeword-based MPA Symbol- Based MPA



3 SCMA: An Introduction

SCMA [9] is a multidimensional codebook based access, based on non-orthogonal

technique, introduced by Huawei Technologies. In this access, the incoming bits are

directly mapped into multidimensional code words and are transmitted across the

channel. The implementation of Link level simulation for SCMA requires only few

modifications to be done on the LTE transceiver [16]. At the receiver end to reduce

the complexity of decoding and avoid the interference of the channels, MPA is used.

SCMA is a technique used in 5G communication system for economic, energy

efficient link layer performance and low complexity implementation [12]. CDMA is a

multiple access in which the data is spread out over orthogonal code sequences. LDS

(Low Density Signature) is a more advanced approach of CDMA. In CDMA, the

CDMA signature expands to a QAM symbol generated from QAM mapper. Whereas

SCMA involves clubbing of QAM mapper and CDMA spreader as shown in Fig.6.

Fig. 6. Clubbing of QAM Mapper with CDMA spreader [9]

At transmitter the multi-dimensional codeword’s are formed by mapping the coded

bits directly in complex domain and codeword’s from different users are overlapped

non- orthogonally in sparse spreading way. Signal detection is done by the receiver

which is then followed by channel decoding for data recovery.

3.1 SCMA System Model

There are J user layers in this system. The signal of each user layer is spread into k

orthogonal resource layers. SCMA transmits the signal in an overloaded manner, i.e.

λ. The log |M| input binary bits bj with unique codebook Xj ⊂ ℂ k are mapped into a

k-dimensional codewords Xj. The codeword’s mapped by input bits correspond to the

codebook of the user layer where different codebook is owned by different users. The

design of encoder involves two steps as shown in Fig.7 and described as given below:



i) Binary bits b j are modulated to d bits from (d0: dN), where g j will be the

modulating generator matrix represented by

dj=bj(gj) . (1)

ii) K-N zeros are mapped in the Xj codeword which is k-dimensional with V j ⋵ B,

k*N matrix as shown in Fig.9, thus expressed as

Xj=Vj(dj) . (2)

Fig.7. Fixed Up-Link SCMA System Model [15]

The SCMA Encoder F shown in Fig.8 maps symbols from V users (1: V) where

each symbol b v is represented by M bits. Codeword is represented as a point in a

modulation constellation where the bv consists of 3 bits; each point in it is represented

by a complex number (r, Ө).

The codeword itself is represented as a very sparse matrix, which determines

where the 3 encoded bits will be transmitted on the available sub-channels (carriers).

This matrix is denoted by B matrix as shown in Fig.9 i.e. B , kxM assuming F

available channels where we use only M bits. Thus B is a matrix, consisting of 0s and

1s where the 1s represent the places where there is transmission.

To construct B we can start with Identity matrix I so that it maps the m symbols to

M codewords. Then all zero columns are inserted to make the matrix sparse.



Fig. 8. V=6, M=4, F=4 [14]

Consider an example for the above design shown in Fig.8 using tanner graph and

the sparse Matrix as shown in the Fig.9

Fig. 9. Tanner Graph and matrix

Number of 1s in each column is denoted by dk that is number of users from which

each subcarrier accepts the data, whereas the number of 1s in each row is denoted by

dv. Table 3 shows the variables used in the tanner graph shown in Fig.9

Table 3. Variables used in Tanner Graph

V 6 No of Layers F=k 4 Number of functional nodes i.e. available subcarriers M 4 Length of codeword in number of bits dv 2 Maximum k nodes connected to each V node (No of

used subcarriers) dk 3 Maximum V nodes connected to each k node λ (k-1)/2=1.5 Overloading Factor

3.2 Design of Codebook

The design of codebook for SCMA is supposed to be joint optimization of multi-

dimensional constellation design, which makes this access unique than the other

NOMA techniques. The basic aim of the codebook design is to maximize the shaping



gain by providing good distance properties in the multidimensional constellation. It

should also have less projection points over each resource element. Multi-dimensional

codebook design has been studied in different aspects and a generalized method to

design a codebook of SCMA system is given in [18]. The Codebook initially was

designed on the basis of 8-QPSK constellation. Another approach of designing an

efficient codebook was using star-QAM signaling constellation [20], which helps in

improving the BER without hampering low detection complexity. A Multi-

Dimensional SCMA Codebook Design Based on Constellation Rotation and

Interleaving [19], which proposes lower BER than the low density signature in down-

link Rayleigh fading channels. The spherical code method, is another approach that

improves the system performance, in order to build mother multidimensional

codebook [21]. The designing equation of the codebook for SCMA is given by [9]:

V *, G*= arg maxV,Gm(S (V,G; J,M,N,K)) . (3)

Where m is the design criterion, in order to achieve sub-optimal solution for this

multidimensional problem, a multi-stage optimization approach is proposed.

SCMA aims at reducing the complexity of SCMA detectors. The detection can be

realized by finding the maximum joint posterior probability of all users’ transmitted

symbols. As a result of enormous computations practical implementation is

hampered. Hence, the Message Passing Algorithm (MPA) [22], which is used in LDS

[23][24] based on the sum-product algorithm [25] is used by SCMA detector to

reduce computation.

In order to reduce the complexity, fixed-point implementation of the log-domain

message passing algorithm (Log-MPA) [26] was implemented. Another proposed

approach used two receivers [27], which simplified the detection structure but also

curtailed exponent operations quantitatively in logarithm domain [15]. Low

complexity of detection and low complexity detection structure due to the codebooks

[28] is studied for the receiver. Fixing t codeword’s in the mth iteration [29] is a

simplified detector based on Partial Marginalization, (IPM-MPA) detector for the

fixed up-link SCMA system. Thus IPM-MPA is more computational efficient than

PM-MPA [29].

3.3 SCMA Link Implementation

By doing minor modifications in the LTE transceiver the link level simulations for

SCMA are implemented. As shown in Fig.10, the change made in the transmitter is

done by replacing the QAM modulator and the DFT block by SCMA encoder which

maps the coded bits into multidimensional codeword. The spreading factor of these

transmitted bits can be seen from the tanner graph as shown in the Fig.9. As seen in

the transmitter only by making few modifications in the LTE receiver, the receiver of

SCMA is designed by replacing single user channel equalization and QAM de-

mapper with SCMA decoder of each layer. Tanner graph constructed by the

codebooks are performed by the MPA algorithm. It starts with the initial conditional

probability calculation at each function node.



Then it enters MP iterations between the function node and the variable node. For

each iteration, both the nodes are updated; this is done independently by each pair.

After several sufficient iterations LLR (Log Likelihood ratio) for coded bits are

calculated based on codeword probability & output at variable node and can be given

as the input to the turbo decoder. Thus the user to user communication in SCMA can

be studied through the Fig.10, and its block diagram is shown in Fig.11.

Fig. 10. Uplink Implementation for SCMA at the transmitter end as compared to OFDMA

transmitter [17]

Fig. 11. SCMA implemented in transmitter and receiver [17]

4 Conclusion

This paper explains the progress of wireless communication towards SCMA as a

promising technology for 5G wireless communication. First, the necessity of SCMA



with its comparison with other NOMA techniques as well as other accesses is briefed

then, structure, encoding, multiplexing, codebook design and link implementation

techniques are described. Connectivity, high spectral efficiency and low complexity

are studied as the key features of SCMA. Sparsity of multi-dimensional codewords

for low complexity of joint detection with high performance at the receiver end can be

resolved with the help of MPA algorithm.

5 Future Scope

FPGA implementation of the encoder and the decoder design can be done for the

practical implementation. Bit Error Rate (BER) vs Eb/No curve can be enhanced as

the bit streams can be decoded with the average BER less than 0.001 (namely at most

1 bit error in the total 1000 bits [17]. Complexity of the receiver can be reduced by

enhancing the encoder design as well as by implementing Max Log MPA at the

receiver. The formation of new codebook can also be one of the factors responsible

for enhancing the transmission. The codebook with other constellations can also be

formed, the Euclidean distance between the points of which satisfies the requirement

stated.

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