Multi-user detection for the downlink of NOMA systems with multi-antenna schemes and power-efficient amplifiers

Physical Communication 33 (2019) 199–205

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Multi-user detection for the downlink of NOMA systems with multi-antenna schemes and power-efficient amplifiers ∗

Filipe Casal Ribeiro a , , João Guerreiro a,b , Rui Dinis a,c , Francisco Cercas a,d , Dushantha Nalin K. Jayakody e,f a

IT - Instituto de Telecomunicações, Portugal UAL - Universidade Autónoma de Lisboa, Portugal FCT - Universidade Nova de Lisboa, Portugal d ISCTE - Instituto Universitário de Lisboa, Portugal e School of Computer Science and Robotics, National Research Tomsk Polytechnic University, Russia f School of Postgraduate Studies, Sri Lanka Technological Campus, Sri Lanka b c

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Article history: Received 19 February 2018 Received in revised form 22 November 2018 Accepted 3 January 2019 Available online 15 January 2019 Keywords: NOMA SC-FDE Iterative frequency-domain detection Multi-antenna systems Efficient power amplification

a b s t r a c t Non-orthogonal multiple access (NOMA) schemes have been recognized as a promising multiple access method for the fifth generation (5G) communication systems. In NOMA, multiple users can share the same physical channel, which allows for a substantial increase in capacity gains when comparing to conventional orthogonal multiple access (OMA) techniques. This paper considers the downlink transmission of NOMA schemes combined with single-carrier (SC) signals. We present a multi-antenna transmission technique that is compatible with highly efficient power amplifiers without requiring any pre-processing. Furthermore, a multi-user detection scheme based on iterative frequency-domain equalization (FDE) is presented. We show that besides the high power-efficiency of the transmission scheme, the system’s performance can be close to the matched filter bound (MFB). © 2019 Elsevier B.V. All rights reserved.

1. Introduction Future wireless communication architectures such as fifth generation (5G) systems must cope with the massive explosion of connected devices, which will require a substantial increase in the spectral efficiency. In the last years, non-orthogonal multiple access (NOMA) schemes [1] have been considered as a solution to increase the systems’ capacity. Contrarily to conventional orthogonal multiple access (OMA) techniques such as orthogonal frequency division multiple access (OFDMA) [2] and time division multiple access (TDMA), where a unique user is served by a single orthogonal resource block [3], NOMA techniques can provide substantial capacity gains, thanks to the fact that multiple users can share the same orthogonal resource block. For this reason, NOMA techniques are being proposed for 5G systems [4–7]. The NOMA concept can be employed in multicarrier and singlecarrier (SC) systems, i.e., in systems when two or more users are served by the same subcarrier or by the same time-slot, respectively. In both cases, users can be separated in the power-domain, leading to the so-called power-domain NOMA [8–10]. In those systems, different signals are transmitted with different power levels ∗ Corresponding author. E-mail address: [email protected] (F.C. Ribeiro). https://doi.org/10.1016/j.phycom.2019.01.003 1874-4907/© 2019 Elsevier B.V. All rights reserved.

to allow for users’ separation in the power domain. At the reception, the user’s separation can be performed by taking advantage of the difference between the power levels, employing successive interference cancelation (SIC) at users with better channel conditions, since the low-power signal is designed to produce negligible interference in the high-power signal and the high-power signal can be estimated accurately and removed when detecting the lowpower signal [11,12]. This approach is particularly interesting for downlink transmissions [13,14], where the base station (BS) must serve in a fairly way different users located at different distances (i.e., with different transmit power requirements) [15,16]. In conventional single-antenna NOMA systems, the signal of each user is weighted with the appropriate power scaling factor and the signals of all users are combined before the amplification process. However, even if the signal of each user is based on constellations with reduced amplitude variations (or even with constant amplitude constellations such as quadrature phase shift keying (QPSK) constellations), the combined signal might have large envelope fluctuations, that can be even aggravated by the filtering process. As a result, to guarantee a linear amplification of both high-power signals and low-power signals, highly linear, energy-inefficient power amplifiers of classes A or B amplifiers must be adopted [17]. However, the large peak-to-average power ratio (PAPR) of the combined NOMA signal prevents the amplifier from working in the maximum efficiency operating point (i.e., close to saturation),

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Fig. 1. NOMA transmission approaches: (i) single-antenna approach with a single amplifier and a combiner, (ii) single-antenna approach with multiple amplifiers and a combiner, (iii) multiple-antenna approach with multiple amplifiers and no combiner.

since a large input back-off (IBO) should be adopted to avoid nonlinear distortion effects. Consequently, the power efficiency can be very low [18]. As an alternative, the amplification can be done separately for each signal, ideally with constant or quasi-constant envelope constellations such as the ones of [19,20]. Under these conditions, each amplifier can operate in the saturation regime, allowing a high power efficiency. However, since the signals must be combined after the amplification, the efficiency gains of the amplification process can be destroyed by the unavoidable combination losses. To overcome this, we propose a NOMA single-carrier downlink scheme designed for highly time-dispersive channel where the signals of the different users are amplified separately and transmitted by a dedicated antenna. Since the signal is combined in the channel, there is no need for a combiner at the transmitter (i.e., at the BS), which means that the combination losses are avoided and we can have a highly power-efficient transmission. At the reception, we consider single-antenna mobile terminals (MTs) that perform the multi-user detection employing SIC receivers [21]. Due to the selectivity of the channel, the frequency domain equalization (FDE) or frequency-domain precoding (FDP) becomes of special importance. SC techniques with frequencydomain equalization (FDE) at each MT, also denoted SC-FDE, are particularly interesting for broadband wireless systems that require high power efficiency [22], and, to the authors’ knowledge, the study of SC-FDE in NOMA environments is very scarce in the literature. Therefore, instead of employing precoding techniques at the transmitter, we consider FDE techniques at each MT. Moreover, aiming further performance improvements, we propose a reception scheme that combines a SIC multi-user detection with a nonlinear FDE technique based on the iterative block decision feedback equalization (IB-DFE) concept [23,24]. Through a set of simulation results, it is shown that in addition of allowing a highly powerefficient transmission scheme, the proposed NOMA system has an excellent performance in severely time-dispersive channels. More concretely, it is shown that the bit error rate (BER) approaches the matched filter bound (MFB) when the SIC multi-user detection is combined with IB-DFE receivers. The organization of this work is as follows: Section 2 describes the considered downlink NOMA system and characterizes the transmitted signals. Section 3 is focused on the receiver design regarding the different NOMA users. In Section 4 a set of performance results is presented and Section 5 concludes the paper. In this paper, the following notations are adopted: bold symbols denote matrices or vectors; IN denote the N × N identity matrix; x∗ , xT and xH denote complex conjugate, transpose and Hermitian of x, respectively. In general, lower-case symbols denote time-domain variables and upper-case symbols denote frequency-domain variables; x˜ , xˆ and x¯ denote the equalized signal, the ‘‘hard decision’’ and the ‘‘soft decision’’ estimates of x, respectively. The expectation of x is denoted by E [x].

Fig. 2. Input back-off (IBO) in the amplification process.

2. System characterization We consider the downlink transmission where one BS transmits simultaneously to several single-antenna MTs (the extension to multi-antenna MTs is straightforward). For a conventional NOMA technique, the signal intended to a given MT is appropriately scaled by a given power factor and all signals are added before being amplified and transmitted by the BS antenna, as depicted in Fig. 1(i) Since both the low-power signals and high-power signals must be amplified linearly, this imposes the adoption of large IBOs (see Fig. 2), which might lead to a very low power efficiency. To allow the use of nonlinear amplifiers that can have much higher amplification efficiency, we can have a single amplifier for the signal intended to each MT and add the signal at the amplifiers’ outputs, as shown in Fig. 1(ii), but this means difficulties with the combiner (i.e., combiner losses and/or linearity requirements). To overcome these difficulties, we consider the structure represented in 1(iii) In that approach, the signal intended each user is amplified separately and transmitted by a dedicated antenna. Fig. 3 depicts the NOMA system proposed in this paper. The proposed NOMA scheme combined with SC-FDE techniques considers has a BS with T antennas transmits simultaneously signals with different power levels to P single-antenna mobile terminals at distinct distances. Moreover, we consider the number of antennas T equal to the amount of users P. It should be noted that this is not necessarily a limitation if there are many active users in the cell (i.e., if the BS requires many antennas), especially when we move to higher frequency bands (i.e., in millimeter wave (mmWave) communications). In that scenario, we can easily pack many antennas in a small area, which is actually the situation of mmWave massive multiple-input, multiple output (MIMO) systems [25,26] as well as of large intelligent surfaces (LIS) systems [27]. In addition, although our system is multi-antenna, we are not exploring the spatial domain for increasing the capacity, as in conventional MIMO systems. This is justified by the fact that exploring the spatial domain

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Fig. 3. Adopted power-domain NOMA downlink scenario.

for separating the different users would require the use of preprocessing, which might further increase the envelope fluctuations of transmitted signals, reducing the amplification efficiency, as well as channel knowledge at the transmitter side, something that is not necessary with our technique (where the channel estimation requirements at each MT are much lower than with conventional MIMO schemes, especially when the transmit antennas are placed together — at most we would have a phase rotation from one channel to the other). As can also be observed in Fig. 3, we assume that the MTs are located at distinct distances. Therefore, to guarantee the same quality of service of each MT in the cell, the BS adapts the power level when transmitting to each MT, which means that the BS transmits with the lowest power for the closest user and with higher powers for distant users. This power control is modeled through different amplification gains. The amplification gain of the tth power amplifier is denoted by ξt . As in conventional powerdomain NOMA techniques, the multi-user detection process is performed differently for the different users. When detecting a given user, the signals from other MTs that are closer to the BS can be considered as noise. However, the signals intended for the high-power users (which are further away from the BS in relation to the user being considered) are seen as interference and should be detected, i.e., a SIC process should be employed. To deal with severely time-dispersive channels, we consider SCFDE modulations [23] and transmitted blocks with N QPSK data symbols. The signal transmitted for the pth user is defined as sp = s0,p s1,p ... sN −1,p

[

]T

,

(1)

The channels between each transmitting antenna and receiving MT are modeled by I uncorrelated multipath components with Rayleigh fading. We define the channel frequency-response between the pth MT and the tth transmit antenna for the kth sub(t ,p) carrier as Hk . The power of the different multipath components is normalized to ensure that

[⏐ ⏐

(t ,p)

E ⏐Hk

⏐2 ] ⏐ ⏐ = 1.

(2)

In our power-domain NOMA scheme, we consider two different scenarios regarding the channels between the T transmit antennas

and a given mobile terminal. In one scenario, the channels between (t ,p) = the tth transmit antenna and a given MT are equal, i.e., Hk (t ′ ,p)

Hk ; this scenario is justified by the fact that the different transmit antennas of the BS can be placed close together (contrarily to conventional MIMO schemes where it is desirable to have uncorrelated channels), which means that one can expect the channels to be identical, up to a phase rotation (that would be small if the antennas are placed one on the top of the other). In the other scenario, the channels between the transmit antennas of the BS ′ (t ,p) and the receive antenna of a given user p, i.e., Hk ̸= Hk(t ,p) are different; this scenario is associated with situations where the BS antennas haver a higher separation, which leads almost uncorrelated channels, as in conventional MIMO techniques. Thanks to a cyclic prefix larger than the channel impulsive response, we can express the received signal for the pth MT and subcarrier k as Yk,p =

T ∑

ξt Sk,p Hk(t ,p) + Nk ,

(3)

t =1

where {Yk,p ; k = 0, 1, . . . , N − 1} is the discrete Fourier transform (DFT) of the useful time-domain block {yn,p ; n = 0, 1, . . . , N − 1}. Moreover, Sk,p and Nk denote the frequency-domain transmitted symbol to the pth MT and the additive white Gaussian noise (AWGN) component associated to the kth frequency, with

[⏐

⏐ ]

2 variances E ⏐Sk,p ⏐

[ ] = 2σS2 and E |Nk |2 = 2σN2 , respectively.

Since we are considering T = P, we assume that the tth transmit antenna transmits to the pth MT. Therefore, the index t (or p) is related to the distance between the MT and the BS: the higher the distance, the lower the value of t, which means that in our NOMA scheme we have ξt > ξt +1 (see Fig. 3). In that context, the power separation ratio (PSR) between any ‘‘adjacent’’ users p and p + 1 would be attained by adopting the amplification gains of the adjacent antennas as ξt and ξt +1 , respectively. Under these conditions, the PSR is hence defined

βlin =

ξt , ξt +1

(4)

and

β = 20 log10 (βlin )

[dB].

(5)

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The power control implicit by the PSR is employed at the BS so as the intended signal is received with the same power at all MTs. 3. Receiver design In this work, we adopt an FDE-based reception for multi-user detection (i.e., inter-user interference cancellation) and intersymbol interference (ISI) mitigation. Relatively to the inter-user interference, our receiver design takes advantage of two facts: (i) a low-power signal produces a small interference in a higher power signal and (ii) a higher power signal can be easily detected and subtracted from a lower-power signal. Consequently, at a given user, the received signals from the MTs can be high enough to be detected (i.e., they are treated as interference) or too low to be detected. In the latter case, the received signals produce a negligible interference, which means that they can be regarded as noise. To deal with such scenario, we have considered a receiver based on the conventional IB-DFE concept [23,28]. The IB-DFE was modified to deal with this particular power-domain NOMA scheme. In general terms, the detection of a given user U concerns a SIC scheme, where the high-power users are detected and canceled, and the low-power MTs produce a negligible interference, being excluded from the detection process. For the lth iteration, the estimation of the user p in the detection of the MT U is expressed as

⎛

p−1

(l)

(l)

S˜k,p = Fk,p ⎝Yk,U −

∑

(l)

(p′ ,U)

S¯k,p′ Hk

U

−

−

¯

∑

(l−1)

(p′′ ,U)

S¯k,p′′ Hk

⎠

p′′ =p+1

p′ =1 (l) (l−1) Bk,p Sk,p

⎞

.

(6)

The feedback is based on the soft-decisions, which can be obtained by the average symbol values conditioned by the FDE output. For the specific case of QPSK constellations, i.e., when sn,p = ±1 ± j, these average values are defined as [28]

( s¯n,p = tanh

LRe n,p

)

( + j tanh

2

LIm n,p

,

LIm n,p =

2

σn2,p 2

σn2,p

Re(s˜n,p ),

(8)

Im(s˜n,p ),

(9)

N −1 1 ∑⏐

2N

N −1 ∑ ⏐ ⏐ ⏐ ⏐s˜n′ ,p − sn′ ,p ⏐2 ≃ 1 ⏐s˜n′ ,p − sˆn′ ,p ⏐2 .

2N

n′ =0

(10)

n′ =0

Naturally, although the soft-decisions are defined in the time(l) domain, they appear in the frequency-domain in (6), where S¯k,p ′ represents the DFT of (7). Furthermore, while index p concerns with the high-power users already detected in iteration l, the index p′′ deals with the estimation from the previous iteration for the users that have not yet been detected at the present iteration. The feedforward Fk,p and feedback Bk,p coefficients, which define the state of the iterative receiver, are given by (l) Fk,p

⏐2 )⏐ (l−1)2 ⏐ (p,U) ⏐ 1 − ρp ⏐Hk ⏐ +

,

(11)

1 SNR

and (l)

(l)

(p,U)

Bk,p = Fk,p Hk

− 1,

SNR =

σS2 , σ + σD2 (k)

(14)

2 N

where σD2 (k) concerns the inter-user interference (IUI) and can be expressed as P ⏐ ⏐ ∑ ) ⏐ (pD ,U) ⏐2 2 ( −2 , ⏐Hk ⏐ σS (pD − p) βlin

σD2 (k) =

(15)

pD =U +1

with pD concerning the interference signals. In general, when user U is being detected, there are U − 1 interference signals and P − U noise signals, respectively. By particularizing (6) for the furthest located user (i.e., for U = 1), which is the user that requires the highest transmit power, the FDE output becomes (l)

(l)

(l)

(l−1)

S˜k,1 = Fk,1 Yk,1 − Bk,1 S¯k,1 .

(16)

Clearly, the modified IB-DFE detection of our NOMA scheme resembles a conventional IB-DFE in a single-user environment. This scenario is illustrated in Fig. 4. It should be noted that regardless of the user being detected, the estimated symbols at the lth iteration {ˆsn(l),p ; n = 0, 1, . . . , N − 1} correspond to the time-domain hard(l) decisions associated with the FDE output {˜sn,p ; n = 0, 1, . . . , N −1} and are computed as sˆn(l),p = sign Re s˜(l) n,p

(

(

))

( ( )) + jsign Im s˜n(l),p ,

(17)

In this section we present a set of results regarding the performance of the proposed NOMA system with iterative FDE receivers. Otherwise stated, we consider SC blocks with N = 256 QPSK data symbols selected under Gray mapping as well as frequencyselective channels with I = 64 uncorrelated multipath components with Rayleigh fading. All BER results are compared with the matched filter bound (MFB), which gives an indication of how close a given performance is from an optimum scenario where there is no ISI and no interference between users. Concerning a given channel realization between with the tth BS antenna and the pth user, the MFB is defined as [29] MFB,H

Pb

⎛ ⎞  N −1  2Eb 1 ∑ ⏐ ⏐ ⏐H t ,p ⏐2 ⎠ . = Q ⎝√ k N0 N

(12)

(18)

k=0

On the other hand, the MFB associated with several channel realizations (which is the one that appears in our results), can be defined as an average of (18) over several channel realizations, i.e., MFB,H

PbMFB = EH Pb

∗(p,U)

= (

When computing the Fk,p coefficient, the signal-to-noise ratio (SNR) is given by

[

Hk

(13)

n=0

4. Performance results

and

σn2,p =

N −1 ⏐ 1 ∑ (⏐⏐ ( (l) )⏐⏐ ⏐ ( (l) )⏐⏐) ⏐Re s¯n,1 ⏐ + ⏐Im s¯n,1 ⏐ . 2N

(7)

where LRe n,p =

ρ (l) =

where the sign(·) function is used to obtain the hard-decisions.

)

2

respectively. The parameter ρ (l) measures the reliability of the data estimates of the lth iteration (it is assumed that ρ (0) = 0, which means that when l = 1 we have a conventional, linear FDE), and is defined as

]

⎞⎤ ⎡ ⎛  N −1  2Eb 1 ∑ ⏐ ⏐ 2 t , p ⏐ H ⏐ ⎠⎦ . = EH ⎣Q ⎝√ k N0 N

(19)

k=0

Concerning a scenario with T = 2 transmitting antennas and P = 2 receiving MTs, Fig. 5 shows the BER performance for the furthest user (U = 1) considering both equal and uncorrelated channels between the BS antennas and that user. The number of

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203

Fig. 4. IB-DFE receiver structure in a single-user environment.

Fig. 5. BER performance for a scenario with P = T = 2, U = 1 and β = 14 dB, with equal and different channels. Fig. 6. Evolution of the channel frequency response at a given user considering: (A) different channels and (B) equal channels.

iterations of the IB-DFE receiver is L = 4 and a PSR of β = 14 dB is considered. For simplicity purposes, the BER performances presented in this paper only show iterations 1, 2 and 4, since the 3rd iteration does not add relevant information regarding l = 4. For the sake of comparison purposes, the figure also includes the performance of a linear FDE receiver in a single-user environment. From this figure, it can be noted that neglecting the low-power signal has a reduced impact on the performance of the IB-DFE detection of the high-power signal, since after L = 4 iterations the performance is close to the MFB, as happens in conventional single-user IB-DFE systems. This means that β = 14 dB is enough to separate the two signals. In fact, after a few iterations, the ISI almost totally eliminated and the performance is close to the MFB. Furthermore, it can be observed that when the channels between the BS antennas and the user are uncorrelated, the performance is worse than when they are equal. This can be explained by the fact that although in average the high-power signal is associated with a better channel, the situation can be inverted locally along the signal bandwidth due the existence of deep fades. This effect is illustrated in Fig. 6, which shows the channel frequency responses associated to a given user when the PSR is β = 14 dB. More concretely, Fig. 6.A shows the evolution of the channel frequency responses when there are different and uncorrelated channels between the BS antennas and the user and Fig. 6.B shows the situation where the channels between the different transmit antennas and the user are equal. Despite the constant difference along the band associated to the PSR, it can be observed that when the channels are different and uncorrelated, the ‘‘best channel’’ (i.e., the one associated with the high-power signal) can be worse than the channel associated to the low-power signal in some subcarriers. Indeed, although

this is a rare event, it can lead to performance degradation. As expected, for the first iteration, the performance associated with the proposed IB-DFE for our NOMA multi-user scheme is worse than the performance associated with a linear FDE receiver (i.e., for the first iteration of an IB-DFE receiver) in a single-user scenario. This can be explained by the fact although the low-power signal associated with the other MT is not taken into account in the detection (i.e., it is not seen as an interference term), it contributes to increase the noise component, which leads to some performance degradation. In the remaining performance results we assume the use of equal channels. Concerning a scenario with T = 2 transmitting antennas and P = 2 receiving MTs, Fig. 7 shows the BER performance associated with the closest user (U = 2) and β = 14 dB. Clearly, with the power separation ratio of β = 14 it is possible to detect both interference and data signals, with the performance associated with the data detection being close to the MFB. To understand the choice of a power separation of β = 14 dB, it is important to compare the performance of our technique to the one associated with the ideal case, i.e., when the closest user knows the data transmitted to the furthest user and performs an ideal interference cancelation. Fig. 8 depicts the BER performance of the closest user considering β = 14 dB well as an ideal scenario where there is perfect cancelation of the IUI from the interfering signal (i.e., the high-power signal). The performance of a linear FDE receiver in a single-user scenario was also included for the sake of comparisons. Clearly, the use of β = 14 dB leads to a BER performance that is almost equal to the one obtained in an ideal scenario where the

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Fig. 7. BER performance for a scenario with P = T = 2, U = 2 and β = 14 dB.

Fig. 9. Required Eb /N0 to achieve BER performances of 10−3 and 10−4 for different values of β .

Fig. 8. BER performance for a scenario with P = T = 2, U = 2 considering β = 14 dB and perfect cancelation of the interfering signal.

closest user makes a perfect IUI cancelation of the interfering signal from the furthest user. Moreover, regarding the first iteration, the performance associated with a perfect cancellation scenario (or a scenario with β = 14 dB), is equal to the one obtained in a conventional single-user, linear FDE scenario. This can be explained by the fact that, in those conditions, the multi-user scenario is converted into a single-user scenario from the perspective of user U = 2. Furthermore, for the same conditions of Fig. 8, we can analyze Fig. 9 in order to emphasize the use of β = 14 dB as a choice for the PSR. Here, regarding the detection of the data signal (U = 2), we illustrate the required Eb /N0 in order to achieve BER performances of 10−3 and 10−4 considering different values of β . As expected, in order to have BER performances of 10−4 , a higher value of β must be considered when comparing to 10−3 . Moreover, β = 14 dB indicates a correct reference of PSR, since with lower values the required Eb /N0 tends to become higher. As observed, higher values of β do not increase the performance significantly when comparing with β = 14 dB. Considering a scenario with P = T > 2, Fig. 10 illustrates the BER performance for P = T = 5 and the data signal U = 3. This means that there are both 2 high power interference signals and noise signals. From this figure it is possible to conclude that our receiver can detect the data signal even with high values of interference signals, with the BER performance being close to the MFB.

Fig. 10. BER performance for a scenario with P = T = 5, U = 3 considering β = 14 dB.

5. Conclusions In this paper we considered the use of SC-FDE signals combined with NOMA schemes in the downlink transmission. We presented a multi-antenna transmission technique that is compatible with the use of high-efficiency, nonlinear power amplifiers and does not require any pre-processing and allows the use of power-efficient amplifiers. Moreover, an efficient detection is achieved using iterative receivers with joint multi-user detection and equalization. Our performance results showed that the prosed technique allows high power efficiency, with BER performance close to the MFB. Acknowledgments This work is supported by the European Regional Development Fund (FEDER), through the Competitiveness and Internationalization Operational Program (COMPETE 2020) of the Portugal 2020 framework, Regional OP Centro (POCI-01-0145-FEDER030588), Regional OP Lisboa (Lisboa-01-0145-FEDER-03058) and by FCT/MEC through national funds, under Project PES3N (SAICT45-2017-02) and Instituto de Telecomunicações project UID/EEA/50008/2013. This work was also funded, in part, by the framework of Competitiveness Enhancement Program of the National Research Tomsk Polytechnic University, Russia.

F.C. Ribeiro, J. Guerreiro, R. Dinis et al. / Physical Communication 33 (2019) 199–205

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Filipe Casal Ribeiro received the M.S. degree in Telecommunications and Computer Science engineering from ISCTE-Lisbon University Institute, Lisbon, Portugal in 2012. He is currently working towards the Ph.D. degree in Information Science and Technology in ISCTE-Lisbon University Institute, Lisbon, Portugal and in the Wireless Communications group of Telecommunications Institute, Lisbon, Portugal, since 2013. His research interests include wireless communications systems and frequencydomain equalization issues in MIMO environments. João Guerreiro (S’15, M’17) received the MSc. and the Ph.D degrees from Faculdade de Ciências e Tecnologia (FCT), Universidade Nova de Lisboa (UNL), in 2012 and 2016, respectively. He is currently an assistant professor at Universidade Autnoma de Lisboa and researcher at Instituto de Telecomunicações. He has been involved in several research projects in the broadband wireless communications area. His research interests include wireless communications, digital communications, multiple antenna systems and digital signal processing for transmission and reception systems. Rui Dinis received the Ph.D. degree from Instituto Superior Técnico (IST), Technical University of Lisbon, Portugal, in 2001. From 2001 to 2008 he was a Professor at IST. Since 2008 he is teaching at FCT-UNL (Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa). He was a researcher at CAPS/IST (Centro de Análise e Processamento de Sinais) from 1992 to 2005; from 2005 to 2008 he was researcher at ISR/IST (Instituto de Sistemas e Robótica); in 2009 he joined the research center IT (Instituto de Telecomunicações). He has been involved in several research projects in the broadband wireless communications area. His main research interests include modulation, equalization, synchronization and channel estimation. Francisco Cercas has more than 34 years of professional experience including more than 30 years of university teaching, 15 at IST and 16 at ISCTE-IUL where he is a Full Professor and the President of the Scientific Council. He is author and co-author of a new class of codes, TCH (Tomlinson, Cercas, Hughes), one patent, 4 book chapters, 14 journal papers, more than 150 conference papers and several research reports, 5 PhDs theses supervision completed, as well as many MsC’s and Final Year’s Projects at both IST and ISCTE-IUL. He is Senior Member of IEEE, Coordinator of the Specialization in Telecommunications of Ordem dos Engenheiros since 2014 and Vice-coordinator of that Engineering Society between 2008 and 2013. He has been a researcher at CAPS, INESC, Satellite Centre of the University of Plymouth (UK) and Instituto de Telecomunicaes, where he is presently a Director of the IT Lisbon pole). His areas of interest include satellite communications, location and positioning, modulation and coding theory, mobile communications and related topics. Dushantha Nalin K. Jayakody (S’09, M’14) received the Ph. D. degree in Electronics, Electrical, and Communications Engineering in 2014, from the University College Dublin, Ireland. He received his MSc degree in Electronics and Communications Engineering from the Department of Electrical and Electronics Engineering, Eastern Mediterranean University, Turkey (under the University full graduate scholarship) and ranked as the first merit position holder of the department, and B. E. electronics engineering degree (with first-class honors) from Pakistan and was ranked as the merit position holder of the University (under SAARC Scholarship.). From 2014 - 2016, he was a Postdoc Research Fellow at the Institute of computer science, University of Tartu, Estonia and Department of Informatics, University of Bergen, Norway. From summer 2016, he is a Professor at the School of Computer Science & Robotics, National Research Tomsk Polytechnic University, Russia, where he also serves as the Director of Tomsk Infocomm Lab. He also serves as the Director of School of Postgraduate Studies, Sri Lanka Technological Campus (SLTC), Sri Lanka. Dr Jayakody has received the best paper award from the IEEE International Conference on Communication, Management and Information Technology (ICCMIT) in 2017. Dr. Jayakody has published over 100 international peer reviewed journal and conference papers. His research interests include PHY and NET layer prospective of 5G communications, Cooperative wireless communications, device to device communications, LDPC codes, Unmanned Ariel Vehicle etc. Dr. Jayakody is a Member of IEEE and he has served as workshop chair, session chair or technical program committee member for various international conferences, such as IEEE PIMRC 2013-2018, IEEE WCNC 2014-2018, IEEE VTC 20152018 etc. He currently serves as an Area Editor the Elsevier Physical Communications Journal, MDPI Information journal and Wiley Internet of Technology Letters. Also, he serves as a reviewer for various IEEE Transactions and other journals.