IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERINGIEEJ Trans 2019; 14: 658–669Published online in Wiley Online Library (wileyonlinelibrary.com). DOI:10.1002/tee.22852
Paper
Cooperative Communications Using Relay Nodes for Next-GenerationWireless Networks with Optimal Selection Techniques: A Review
Keywords: cooperative communication; IoT; mm-wave; relay selection node; user equipment; virtual MIMO
Received 5 February 2018; Revised 13 September 2018
1. Introduction
Nowadays, the increase in demands of the high data ratein wireless communication is a challenging task to networkoperators. Consequently, new methods and techniques are neededto accomplish the demand of high data rates. The innovativetechniques must be very efficient, reliable, and cost-effectiveto achieve the goals of the next-generation wireless commu-nication [1]. However, wireless communication faces a lot ofchallenges such as multipath, fading, and distortion. The effectsof multipath and fading can be overwhelmed by using differentdiversity techniques. However, these diverse techniques must becapable of generating a good performance.
Transmit diversity is one of the reliable techniques to counterdown the effects of fading by means of more than one antenna atthe transmitter side [2]. Regarding transmit and receive diversity,the use of multiple-input and multiple-output (MIMO) is apromising method to combat against fading and to increase thecapacity even in the multipath prorogation environment. However,different factors like power, cost, and size, as well as weightlimitation, make it difficult to abundantly utilize the benefits ofMIMO. To overcome those problems, another so called techniquevirtual MIMO recognized as Cooperative Communication thatengenders this diversity in a better and cost-effective way wasused [3]. The rudimentary concepts of cooperative communicationare well presented by Cover et al. [4]. The ability of more thantwo nodes network that contains a source and a relay node (RN)
Department of Computer Engineering, Kocaeli University, 41380 Kocaeli,Turkey
is that it transmits the duplicates of a signal to the destinationindependently. Many ideas regarding cooperative communicationwere first derived by Nichola et al. [5]. In the next-generationwireless network, cooperative communication may be one of thepromising approaches for achieving the high data rates as well asefficient utilization of the bandwidth. Cooperative communicationuses a RN, to provide coverage in the holes within the Long-TermEvolution-Advanced (LTE-A) cellular networks [6]. Similarly, inmm-wave communication that is considered in 5G, the relayingtechniques are used to overcome different challenges of linkblockage, backhaul connectivity, and path loss etc. Moreover,to make this technology more efficient and reliable, furtherimprovements are required to achieve these goals.
This study presents a broad overview of different relayingprotocols with optimal relay selection methods used in differentwireless networks. In addition, this study presents the potentialbenefits of using cooperative communication to overcome differentchallenges faced by the next generation of wireless networks. Theremainder of this article is organized as follows. Section 2 presentsexisting research on cooperative communication. Section 3 givesan overview of cooperative communication, in which differentrelaying protocols are presented and comparison between them. InSection 4, we discuss the review of optimal relay selection tech-niques. In Section 5, we explain the different challenges faced bymm-wave and how to overcome them by cooperative communi-cation. Section 6 summarizes the future challenges in cooperativecommunication and finally the conclusion is given in Section 7.
2. Related Studies
Sami et al. [7] demonstrate a survey and taxonomy on mediumaccess control for cooperative communication. This study classifies
COOPERATIVE COMMUNICATIONS FOR NEXT-GENERATION WIRELESS NETWORKS
Table I. Existing research surveys on cooperative communication
Study FrequencyEnergy
efficiency Domain Protocols MAC Fairness Security
Sami et al. [7] Broadband Yes VANETs Yes Yes Yes YesGlass et al. [8] Broadband No VANETs Yes No No NoKerrache et al. [9] Broadband No VANETs Yes No No YesCichon et al. [10] Broadband Yes Mobile Tel. No No No YesAhmed et al. [11] Broadband No VANETs Yes No No YesSilva et al. [12] Broadband No MANETs Yes No No YesHong et al. [13] Broadband Yes Wireless networks No No No NoGomez et al. [14] Broadband No VANETs Yes No No YesMansourkiaie et al. [15] Broadband No Wireless networks Yes Yes No NoZhang et al. [16] Broadband No Wireless networks No Yes No NoThis study Broadband and mm wave Yes Multi wireless networks Yes No Yes Yes
MAC protocols into two major categories such as contention-basedand noncontention-based protocols depending on the mechanism ofobtaining channel access. Moreover, this study narrates the currentstate of the art of MAC protocols for cooperative communication.A review of the cooperative cache for vehicular networking isdemonstrated in [8]. This study classifies current caching discov-ery techniques and their benefits in VANETs. Existing securitysolutions fall into two categories namely trust and cryptography.Trust is a complement to cryptography on some models wherethe latter fails to neutralize all potential attacks. In [9], a sur-vey on existing trust models for cooperative vehicular networksis presented. The authors show existing trust models and howthey are implemented in vehicular networks. The quest for energyefficiency in cooperative spectrum sensing is surveyed in [10].The authors in [10] classify potential solutions to the problem ofcooperative spectrum sensing with respect to energy efficiency.The most recent survey of cooperative vehicular networks is pre-sented in [11] wherein factors such as routing protocols, MAC,scheduling, and security are demonstrated. Silva et al. [12] pro-vide a review of cooperative strategies for challenged networksand applications. They consider factors such as network delay,bandwidth limitations, noises, disconnections, interference, stor-age capacity, and power. A tutorial survey on different power andbandwidth allocation techniques for cooperative communicationsis demonstrated in Ref. [13]. The authors compare these tech-niques and demonstrate their suitability in resource-constrainednetworks such as wireless sensor networks. Gomez et al. present areview of cooperative diversity considering the theoretical frame-work and the existing medium access control strategies [14]. Pro-tocols that take into consideration the existence of cooperativecommunication at the physical layer are known as cooperativerouting protocols. Mansourkiai et al. present a review of exist-ing cooperative routing protocols. This survey explores a taxon-omy of cooperative routing protocols and the weakness of eachprotocol [15].
A survey on cooperative single-carrier frequency division mul-tiple access (FDMA) is presented in Ref. [16] wherein the mainconcept of both user cooperation and cooperative single-carrierFDMA is discussed. This survey considers factors such as networktopologies, resource allocation, signal processing, and transmis-sion mode applicable in cooperative communication. Discussionsfrom Ref. [16] demonstrate that relaying in LTE Advanced opti-mally exploit the resources and it is a promising solution foruplink data transmission. In Table I, we provide a summary ofthe existing surveys on cooperative communication. Unlike exist-ing research publications, this study presents a comprehensivereview on cooperative communication taking into considerationthe features of the next-generation mobile networks such as the useof mm-wave.
R
S D
Channel h2
Channel h1
1
2Y
Y
Yx
3
Channel h3
Fig. 1. Relay channel model
3. Cooperative Communication
There are different challenges in a wireless communicationchannel that reduce the performance and efficiency of the wire-less network. To overcome these challenges, cooperative com-munication is considered to be one of the reliable solutionsin terms of cost, size, and spectral efficiency. The coopera-tive communication technology requires numerous nodes trans-mitting signals to the destination. There are different back-and-forth between transmitting signals and power in cooperativecommunication. However, it proposes a substantial performancein terms of enhanced capacity, better-quality transmission relia-bility, and spatial diversity [17]. However, additional power isessential for each cooperative node to transmit both for itselfand also for other nodes. The advantage of diversity gain fromcooperative nodes allows decreasing transmit power, and therebysustaining the same performance. This technique states a systemwhere cooperative nodes coordinate with each other to utilize theirresources to enrich the quality of transmission information [18].
The basic idea of cooperative communication is demonstrated inFig. 1. In the first step, source (S ) broadcasts the message signal(x ) to the destination (D) as well as to the RN (R). In the next step(R) RNs process the received message signal (x ) by using differentrelaying protocols, and then forwards to a destination with theaddition of noise (n). At the destination side, both signals fromthe source and RNs are combined to enhance the performance.
Y1(SD) = xh1(SD) + n1(SD) (1)
Y2(SR) = xh2(SR) + n2(SR) (2)
Y3(RD) = xh3(RD) + n3(RD) (3)
Rtx = Y1(SD) + Y3(RD) (4)
In (1), Y 1(SD) is a received signal from the direct link (S )to (D) where (x ) is a transmitted message, and h (SD) is thechannel coefficient between (S ) and (D) with Additive WhiteGaussian Noise (AWGN) [19]. Similarly, in (2), Y 2(SR) is a signalfrom (S ) to (R) with also the addition of noise in it. Different
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R
S D
Fig. 2. Amplify and forward method
relay protocols are used on RN for forwarding the informationto (D). Regarding performance and computational complexity,every relaying protocol has gain and some drawbacks that willbe discussed later in detail. In (4), both signals Y 1(SD) and Y 3(RD)
are received and from a combined cooperative signal (Rtx ), whichleads to a better performance. Moreover, different receive diversitytechniques can be used at the receiver side.
There is a different trade-off in terms of complexity andperformance among the diversity techniques such as MaximalRatio Combiner (MRC), Maximal Likelihood (ML), or SelectionCombining (SC) [20]. In relaying protocols, the RNs performa significant role in processing the signal and forward therequired information to a destination in such a manner that itgenerates efficient outcomes [17]. However, there are some setof rules and procedures for forwarding the required informationto the destination. The different types of relaying protocols incooperative communication have a different trade-off that dependson the efficiency, reliability, cost, and performance, etc. The basiccooperative relaying protocols are discussed in this section.
3.1. Amplify and forward method One of the maincooperative relaying protocols is the amplify-and-forward (AF)presented by Lanema et al. 5. The AF relaying protocol canalso be recognized as a booster for forwarding the information,or layer one relaying protocol [21]. AF was divided into twoprocessing phases, in the first phase, the process of amplificationis done at the RN, and in the second phase, the amplified versionof information is forwarded to the destination. The receiver atdestination accumulates all the information sent by the source aswell as RNs, for the final decision on the transmitted signals asshown in Fig. 2. The major drawback of the AF relaying protocolis that noise is also amplified in the cooperative network thatoriginates different complications between (S ) and (D) channelin terms of intersymbol interference (ISI) [22]. One of the reasonsbehind the ISI is the amplified version of the noise signal receivedat (D) by different multipath, which causes different delays [23].In mathematical form, the function of AF is given by, [24].
fAF(Y2(SR)) = βY2(SR) (5)
where β is the (R) transmit power and ƒ is the amplificationfunction. β can be derived as explained by Laneman et al. [25].
β ≤√
PR
h2SRE [|x |2] + E [|nSR |2]
(6)
where PR is the constant average transmit power of (R). Assumingunit variance in AWGN in (6) can be rewritten as
β ≤√
PR
h2SR Es + 1
(7)
The AF protocol has low computational complexity because itinvolves less processing at the RN. As a result, the low computa-tional attribute of AF reduces the net cost of the RN. Furthermore,the duration of delay for forwarding the information to (D) is low[26]. In the fast communication application scenario, the AF is thebest solution. Moreover, the AF relaying protocol is considered
R
S D
Fig. 3. Decode and forward method
as less energy consuming and efficient, which ensure long batterylife especially in terms of wireless sensor networks [27].
3.2. Decode and forward method The Decodeand Forward (DF) cooperative relaying protocol is more complexand progressive when compared to AF [21]. Moreover, in otherwords, it is also recognized as a layer two relay technology thatwas introduced by Sendonaris et al. [28] as illustrated in Fig. 3.In general, the mathematical form of DF can be written as
fDF(Y2(SR)) = x (8)
In (8) x is the message signal extracted by the RN thatsubsequently performs DF functions [29]. In terms of differentmodulation schemes, the function of DF simply can be written asshown in (9) with sgn function [30].
fDF(Y2(SR)) = sgn(Y2(SR)) (9)
Moreover, the performance of the DF relaying protocol can beaccomplished by employing parallel coding and permitting RNs toa make change in the channel coding according to the requirementof the network [31].
The DF relaying protocol can be divided into two different steps.In the initial step, the received signal on the RN is demodulated thatfollows the procedure of encoding. The noise combined with thereceived signal is removed in this step as a result, the amplificationof noise is not carried out by the RN [29]. The amplificationmitigating in noise comes up with several advantages. It reducesthe chance of ISI that leads to less probability of interference inthe cooperative communication network [22]. In the second step,modulation is accomplished on the required information signal andthe process of encoding is done for transmitting the signal to thedestination. Consequently, these stages ensure communication tobe reliable and more efficient. However, the main shortcoming ofthis approach comes up as a processing delay, because the RNrequires additional time for processing the received signal [32].
In the cooperative DF-relaying protocol, the processing delaycan further be distributed into two parts. In the first part,the received signal at the RN follows the entire procedure ofdemodulation, decoding, subsequently modulation, and encoding[33]. Furthermore, if there is an error in the received signal, it isimproved by the error-correcting code. However, there is a trade-off between delay, accuracy, and reliability. In some applications,the processing delay is not considered to be so important. However,the reliability of the information is more essentially required [34].
In the second part, it is not necessary to track all the processof DF-relaying protocol as mentioned above to manage the delaytime. There are certain reasons including the less computationalcapability of the RN, and moreover, some application cannotendure more delay. Hence, the required signal is impartiallydecoded and re-encoded symbol by symbol. In both scenarios,there are different trade-offs depending on the requirements of thecommunication system [27].
3.3. Coded cooperation The coded cooperation relayingprotocol is more efficient and reliable as compared to AF and DFrelaying protocols. It is also referred to as layer three relay tech-nology [21]. Coded cooperation basically incorporates cooperation
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R
S D
Re-encoded parity
Fig. 4. Coded cooperation method
into channel coding [35]. In coded cooperation, the process is per-formed by dividing individually user’s code word into differentparts, for transmitting it through two different independent fad-ing routes [36] as shown in Fig. 4. The elementary principle ofcoded cooperation is that individual RN tries to transmit incre-mental redundancy to other RNs in the network [35].
In cooperative communication, the coded cooperative modedivides the information into different parts by means of segmen-tation [36]. Furthermore, each segmentation is considered as oneblock that is integrated by a cycle redundancy check [17]. Corre-spondingly, the duration of data transmission is also alienated intotwo time slots for each bit of segment, known as the frame [37].In some cases, when the cooperative mode is not required on thecooperative RNs in a network, the code cooperation regresses to anoncooperative mode. The efficiency of coded cooperation is betterbecause processes are repeatedly performed with the help of codedesign during the transmission time [38]. Moreover, no feedbackis required between the relay station and the ultimate destination.The process of coded cooperation is illustrated in Fig. 4, where therelay station generates re-encode parity bits for transmitting it tothe destination. The major drawback of coded cooperation is theincrease in the processing time for performing all these operations,as a result, the delay time factor will increase [39]. However, accu-racy and reliability of the communication system are much better inthis approach. Moreover, coded cooperation reduces interference inthe cooperative network [40]. Figure 5 illustrates the coded coop-eration method for two users UserA and UserB. In this method,each user data is given a precise time slot of one frame for theinterval of transmitting a specific number of bits.
In the first slot, the UserA transmits its data bit1, and in thesecond time slot, the UserB data are sent, i.e., bit2. In case if thecooperative mode is not required during transmission of data, thenUserA transmits its own data in the second time frame, as a matterof fact, in both cases, spectrum efficiency increases [41]. Moreover,in the coded cooperative relaying protocol, the reliability of thecommunication system increases with better utilization of the givenspectrum [42].
3.4. Cooperative relaying protocols and performanceof multirelays In cooperative communication, the overallperformance increases as compared to the noncooperative node [3].The different relaying protocols while combining with a numberof RNs also have a better impact over the performance [43].
In a cooperative relay network, the linear addition of RNs hasbetter average bit error rate (BER) even if the direct channel isin deep fade [44]. In Fig. 6, a general overview is given in whichmultiple RNs R1, R2, R3, and Rk exist between S and D . The
UserB
UserA
UserA
data User B data
Frame 1 Frame 2
UserA
data UserB
data
Frame 1 Frame 2
Base station
Fig. 5. Coded cooperation method between two users
Rk
S D
R3
R1
R2
3h
2h
1h 1h
2h
3h
kh kh
Fig. 6. Scenario of multiple relays
received signals from RNs as well form source at the destinationwritten as follows [24].
Yk(S Rk ) = xhk(S Rk ) + nk(S Rk ) (10)
Yk(RkD ) = x hk(Rk D) + nk(Rk D) (11)
where hk(S Rk ) and hk(Rk D) are the channel coefficient betweensource to RN Rk and destination.
Yk(RkD ) = Gk x hk(Rk D)Yk(S Rk ) + nk(Rk D) (12)
Gk = ES /(ES |hk(Rk D)|2 + N0) (13)
where Gk is the gain between Rk and D and E S is the averageenergy per symbol [45]. Now, at the receiver destination side byusing the maximal ratio combining (MRC) the end to end signalto noise ratio (SNR) can be written as below [46].
αD = α(SD) +N∑
i=1
α(S Rk ) α(Rk D)
1 + α(S Rk ) + α(Rk D)
(14)
where α(S Rk ) = |hk(S Rk )|2ES /N0,α(Rk D) = |hk(Rk D)|2ES /N0 andα(SD) = |hk (SD)|2E S /N 0 are the instantaneous SNR.
All RNs from R1 to Rk have different channel conditions witha different propagation environment including the factor of noise.The challenging task is to find out the optimal relay among them,which shows a better performance over multiple relay cooperativediversity [47].
4. Relay Selection Techniques
The relay selection technique in cooperative communication hasa great impact on the performance of the network. Initially, it isessential to recognize for a RN that when and to whom it willcommunicate [48]. One of the efficient approaches is a prerelayselection technique that follows the RN selection technique beforecarrying out the actual transmission, i.e. training bits are usedto find out the channel condition [49]. In prerelay selection, thebasic point is to update channel state information (CSI) either fromsource to destination or any RN [50].
It is probable that a particular selected RN might not remainoptimal because of variation in the channel or some obstacle makean indirect channel in deep fade. The effect of outdated CSI onthe performance is explored by Vicario et al. [51], whereby itis revealed that the outdated CSI prompt significant performance
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degradation. However, if the prerelay selection is established onthe updated CSI, then the results will be more efficient [52]. In themajority cases, the CSI is not considered during the transmissiontime [53]. In Proactive-Relay selection technique, the updated CSImust be considered during the actual transmission of the dataotherwise the optimal RN may not be the best RN in the network.Moreover, the anticipated quality of services (QoS) may not beachieved. The computational complexity increases if the number ofRN turns out to be more in the cooperative network. This degradesthe performance of the overall system, hence the optimal relayselection is essentially required in the network [54].
4.1. Review of optimal relay selection methods Theoptimal selection of the RN has a great impact on overallperformance of the cooperative wireless network in a relationshipwith efficiency, higher data rate, throughput, efficient energyconsumption, BER, and reliability [55]. An appropriate choice ofthe RN is based on different channel metrics such as CSI, BER,and SNR. The minimum capacity of all relaying nodes can beincreased by finding the optimal RNs between the source anddestination [50]. The choice of selecting the best RNs amongmany candidate RNs is a challenging process. In some cases,the proposed methods are restricted to a single source and adestination pair that are not certainly extended, if there aremultiple sources to destination pairs [56].
S. Hussain et al. proposed two methods for relay selection tooptimize the total transmission time with a constant amount ofdata [57]. The selected relays can be determined by the realizationof the channel condition between the source and the relay station.On the other hand, YiShi et al. came with a different approachbased on ‘linear marking’ by giving the name as an optimalrelay assignment algorithm. The polynomial time base solutioncan achieve the optimal relay selection, even when the number ofrelays is less or more in the cooperative network [50].
Ivos et al. proposed smart relay selection schemes to overcomethe performance degradation problem when spatial informationchannels are correlated in a MIMO environment [58]. The relayselection method based on the eigenvalue properties also decreasesthe processing complexity of user equipment (UE), at the receivingend. However, the efficiency and performance are not achieved,especially in the case of frequency-flat fading channels [59].
In a multiple relay environment, Salama et al. [60] proposedthe best relay selection technique based on the highest SNRover independent nonidentical Rayleigh fading channel. Moreover,the cochannel interference was eliminated by using orthogonalchannels in relationships with time slots, codes, and carriers. Qabaset al. [61] accomplished a better average symbol error rate by
using a moment generating function through which the optimalrelay was selected. Mohammad et al. proposed a reliable relayselection scheme based on calculating the Euclidean distance (ED)among received signals and all the active and nonactive channelscoefficient [62]. Bahareh et al. [63] suggested a novel scheme forthe optimal relay selection process in a different manner by usingcontract theory. The selection criteria were based on minimizingthe link cost in terms of throughput and QoS metric.
In aeronautical communication, the variations in wireless chan-nel are high and the channel continuously changes with time. Therelay selection must be updated to achieve the best performance.Bletsas et al. considered two CSI-related cases, firstly the chan-nel condition during relay selection and secondly, during the datatransmission [64]. The choice of the best relay method is basedon the opportunistic relay selection strategy that is directly relatedto the end to end performance of the network [65]. To overcomethe problem of less performance, a new technique namely repeatedrelay selection is proposed that is based on updated CSI. It is shownthat the throughput of updated CSI is much better as compared tooutdated CSI [66].
Table II summarizes optimal relay selection methods with abrief overview of different wireless application scenarios underdifferent communication metrics. In Zhou et al. survey increasein throughput with a better performance of the wireless ad hocnetwork is achieved by selecting the best relay in the networkbased on updated CSI [67]. In Liu et al. [68], they proposed arelay selection that countered down the effect of eavesdroppingin a cognitive radio network, which is analyzed using channelpower gain. Li et al. [69] proposed a relay selection in thecellular network to overcome the problem of end user degradingperformance and power issue at the cell edge, which is basedon the efficient energy mechanism. In device to device (D2D)communication, the extension in the coverage area and increasein the throughput at the cell edges are achieved by the best relayselection technique [70]. Miao et al. [71] proposed a relay selectiontechnique by utilizing AF and DF relaying protocols with a full-duplex mode. Luo et al. [72] focussed to efficiently utilize theenergy in a wireless sensor network by selecting the best RNbased on the routing algorithm. Zhang et al. [73] proposed thebest relay selection based on updated CSI and higher SNR for the5G wireless network.
4.2. Optimal relay selection for secure cooperativecommunication In a cooperative network, security con-straints and measurement must be taken into account for a reliableand efficient end to end communication. In a distributed coopera-tive network environment, the process of selecting the best relay
Table II. Summary of the optimal relay selection method with different wireless application scenarios
Zhou et al. [67] No Yes Yes No No Ad hoc networks CSILiu et al. [68] No Yes Yes No Yes Cognitive radio
networkChannel power gain
Li et al. [69] No Yes Yes No No Cellular networks Energy efficiencyDeng et al. [70] Yes No Yes No No Device-to-device
(D2D)Power constraint
Miao et al. [71] Yes Yes No Yes No Cooperative relaynetwork
Outage performancegains
Luo et al. [72] Yes No Yes No No Wireless sensornetworks
Network energyefficiency
Zhang et al. [73] Yes No Yes No Yes Fifth-generation (5G) SNR & CSI
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during the transmission of data is highly vulnerable to maliciousattacks that generate a lot of security threads [74]. In some scenar-ios, the eavesdropping link node may have a good channel qualityfor attracting in the selection process of the RN and aims to acquirethe information during the communication process [73]. Therefore,different techniques must be used to overcome the different secu-rity loops in the network. Consequently, some promising methodsare proposed in [75] to enhance physical layer security against theeffects of eavesdropping.
The higher secrecy capacity could be achieved by artificial noiseduring the transmission of data to confuse the fake elements inthe network [76]. Long et al. studied that the secrecy capacity isincreased by combining the optimal relay selection method withartificial noise [77]. Xiao et al. proposed the best relay basedon full and statistical eavesdropping CSI to derive closed-formsecrecy outage probability (SOP) [78].
The mutual sharing of information between all the authenticnodes in the cooperative network is very obligatory to updatetheir current status by theoretical derivation [79]. Kuhestani et al.proposed that joint information sharing can be attained by powermanagement and eavesdropper for the secure optimum relay[80]. Yan et al. proposed secure best relay selection based oninstantaneous CSI that counters down the effects of eavesdroppingas well as interferences [81]. The optimal secure relay was anapproach to multidestination in terms of securing the informationand decreasing the effect of eavesdropping [82]. Zou et al.proposed that the relay selection scheme secures both the primaryand secondary user in the cognitive radio network to improve theperformance and reliability of the network [83].
5. Optimal Relay Selection for Next-GenerationWireless Networks
In different wireless networks such as the cognitive radionetwork, heterogeneous network, and homogeneous network,the selection of best relay can increase the overall performanceof the wireless communication [84,85]. In the cognitive radio net-work, the cooperative spectrum sensing and transmission of dataaim to sense the idle band to facilitate secondary users through anoptimum relay selection technique [86].
In a heterogeneous cooperative network, there are numerousUEs that increase the complexity of the entire system [87]. TheUEs have less power and low computational capabilities, hence theoptimal cooperative RN is highly required to utilize less powerand reduce the complexity of the network [88]. However, it isunrealistic to scan all the UEs for the selection of the best RN in thecooperative network. Yinshan et al. consider both heterogeneousand homogeneous cooperative networks, where the optimum RNis being nominated on the basis of QoS with lower powerconsumption and a high SNR threshold-based structure [89].
Zhang et al. suggested the optimal relay selection techniquefor 5G to decrease the complexity that was established on thereceived power of RNs with the average link information of sourceeavesdropper [90]. Nguyen et al. [91] proposed two relays jointlyselected to secure the information as well as to achieve betterperformance in the cooperative network. Swain et al. analyzedthe performance of the optimal relay selection technique basedon the harmonic mean of total SNR in a wireless network[92]. Kawabat et al. proposed best relay selection constructedbased on the residual energy mechanism for internet of things(IoT) for less and better energy utilization [93]. Ma et al. [94]discussed an efficient technique of optimal relay selection utilizedthat is based on the cross-layer approach to overcome differentchallenges in D2D communication to upgrade the capacity oftraffic offloading.
Available 25 GHz of potential bandwidth
Current spectrum of wireless mobile
communication (3 GHz)
Water vapor absorption
band (164–200 GHz)
Oxygen absorption band
(57–64 GHz)
54 GHz 90 GHz 99 GHz
Fig. 7. Spectrum availability of 3–300 GHz in mm-wave
Primary relay node Secondary relay node
Full duplex relay Half duplex relay
Fallback Relay node linkDirectional
antennas
Link blockage solution
Active relay node Passive relay node
Fig. 8. Possible solutions of link blockage in mm-wave
5.1. Cooperative relaying for mm-waves The nextgeneration of wireless network requires a high spectral efficiencyand a huge bandwidth for increasing the capacity. The currentspectrum between 300 MHz and 3 GHz is already full becauseof several key advantages that are often referred as ‘sweet spot’[95]. Therefore, new methods and techniques are required tofind out the new opportunities to enhance the spectral efficiency,extension in the coverage area, fulfilling the demand of hugebandwidth, reliability etc., to meet the standard requirement of 5G.
In terms of bandwidth requirement, the mm-wave has hugepotential to fulfill the demand of the next generation of the wirelessnetwork [96] as shown in Fig. 7. However, the realization ofthis idea is difficult because of several technical challenges toimplement and utilize the bandwidth effectively [97].
The basic challenges faced by mm-wave are path loss, propa-gation loss, link blockage, power consumption, limited coveragearea, and implementation design issue etc. [98]. In terms of linkblockage, three possible solutions are available to overcome thischallenge as shown in Fig. 8. In the first option, the link blockageis tackled by a technique known as ‘fallback’. In fallback, the pro-cess of switching is performed between the mm-wave band andthe microband until the blockage of the link is not cleared [99].In the second option, two types of RNs (active and passive) areused to overcome the link blockage. These RNs are added in thenetwork and link blockage is eliminated by an alternative path inwhich no obstacle exists between the source and destination [100].
Congiu et al. compared between the fallback and the RN linkand showed that for a high data rate traffic demand, the relayinglink option is more superior [101]. In the passive relay type, no
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Fiber link
Gateway
Blockage
Mm-wave relaying in small cell
IoT cloud
D2D M2M
V2V
Micro BSCore
network
Fig. 9. Mm-wave relaying for outdoor communication
power consummation is utilized and cost of the reflecting materialis not so much expensive as compared to active relay [102]. Themechanism of the passive relay is to reflect the incoming signaltoward the appropriate direction [103]. Wahab et al. analyzedthe coverage in nonline of sight (NLOS) by using a passive RNin mm-wave band having a gain of 20 db [104]. Biswas et al.eliminated link blockage by selecting the best path with thebest relay selection. The optimal relay deployment in mm-waveincreases the coverage area and capacity of the network [105].Zheng et al. discussed the specific 60 GHz band of mm-wave toovercome the link blockage and for better connectivity by optimalrelay selection [106].
The third option for clearing link blockage is installingdirectional antennas in the network. Singh et al. proposed linkblockage mitigation and path loss by deploying a directionalantenna [107]. On the other hand, this option is not suitable forNLOS of communication. The three possible solutions for linkblockage have their own advantages and disadvantages. However,mm-wave with a relaying technique is the most convenient ascompared with other options.
5.1.1. Backhaul connectivity with mm-wave cooperativerelaying In outdoor communication, especially in the denseurban area, the mm-wave spectrum band experiences differentchallenges. However, a lot of opportunities and advantages makemm-wave a promising approach for the next generation of wirelessnetwork. Moreover, the cooperative wireless backhaul connectivityin mm-wave communication is a better choice as compared towired backhaul connectivity due to the costly installation process.Figure 9 shows that the outdoor 5G wireless network havingD2D, vehicle-to-vehicle (V2V), machine to machine (M2M), andbackhaul connectivity in the small cell can be used by employingcooperative relays. Wei et al. highlighted different challenges interms of NLOS, high path loss, and link blockage to design themm-wave backhaul [108]. Sahoo et al. proposed the multihop RNfor backhauling in the 5G of the cellular network. The traffic loadand quality of link were added to maximize the performance ofthe network [109]. Yang et al. proposed multihop cooperative RNsfor outdoor communication aiming to extend the coverage areaand increase the end to end performance [110]. The optimal relaysection can be deployed by evaluating the link blockage probabilityusing geometric analysis in mm-wave communication [111].
5.1.2. Elimination of link blockage in indoor communica-tion with mm-wave cooperative relaying In the next genera-tion of the wireless networks, the target of 10 Gbits/s for the indoor
environment without mm-wave seems difficult to be achieved.However, as compared to the conventional micro frequency band,the mm-wave has high penetration losses for different obstacles.In indoor communication, the penetration losses for the ceiling,walls, door, window etc. vary with the different frequency bandsof mm-wave. Deng et al. analyzed the indoor path loss for theband of 28 and 73 GHz [112]. Table III shows the brief summaryof cooperative relaying in mm-wave communication. The band of60 GHz was considered being most suitable for the indoor envi-ronment for achieving high data rates [113]. However, the lossesstill exist that need to be overcome. Alkhawatra et al. proposed atechnique to reduce the losses and extend the connectivity in the60 GHz band by employing cooperative RNs. It was demonstratedthat the deployment of the RN in the middle of the ceiling of theroom can maximize the performance of end user [114]. The betterconnectivity and link blockage problem were overcome in 60 GHzof the band by aiming to reduce the number of RNs in the network[106]. Saha et al. [115] consider a number of rooms, offices, halletc. for an experiment in 60 GHz of the band with two types ofRNs, a primary node and a secondary node in the network. Theprimary node connected with the wired link of the backbone net-work and a secondary node with a wireless link for the purpose ofimproving reliability, coverage, and capacity. Figure 10 shows apossible solution for indoor communication in the mm-wave band.A Home eNodeB (HeNB) is connected to the backbone networkvia an optical fiber link. Inside the buildings, the rooms are con-nected with a number of RNs via a wireless link. The UE canbe connected by different RNs to avoid NLOS and link block-age. Similarly, the concept of mm-wave with an optimal relayingtechnique is proposed to overcome different challenges such asshared users distributed antenna system (SUDAS), and Shared UEside distributed antenna component (SUDAC) [116]. However, insuch a case, only the fixed relay installed at an optimal locationcan generate better results. Sing et al. 117 proposed a multihopcooperative relay MAC protocol for best network link connec-tivity in both stationary and nonstationary obstacle environments.They showed that the centralized access point and high directionallink maximize the performance.
6. Future Challenges
There are certain future challenges to implement cooperativerelaying for a better performance. The brief overview of the mainfuture challenges is outlined below.
6.1. Interference management In cooperative commu-nication, interference management is a challenging task. The coop-erative RN may possibly suffer from cochannel and adjacentchannel interference. The use of the AF relaying protocol for thepurpose of less complexity mechanism at one end can increasethe amplification in the noise, which introduces interference in acooperative network. In a distributed cooperative network, manyRNs have incomplete knowledge of the overall network and flood-ing of information boost interference in the network. A propermechanism is required to tackle the interference management issuefor a better performance.
6.2. Power optimization The increasing number of RNsin the cooperative network for efficient communication and abetter end to end connectivity utilizes more power. A networkwhere nodes have limited battery power needs to have a poweroptimization mechanism.
6.3. Channel estimation In the literature, the optimalrelay selection generally considers static channel condition. How-ever, in real-time scenarios, the channel is time varying and chan-nel estimation is a challenging task. The CSI is highly required
664 IEEJ Trans 14: 658–669 (2019)
COOPERATIVE COMMUNICATIONS FOR NEXT-GENERATION WIRELESS NETWORKS
Tabl
eII
I.Su
mm
ariz
edov
ervi
ewof
mm
-wav
ew
ithco
oper
ativ
ere
layi
ngte
chni
ques
Com
mun
icat
ion
scen
ario
sR
elay
node
type
sD
uple
xm
ode
Cha
lleng
esC
ost-
effe
ctiv
enes
s
Stud
ies
Indo
orO
utdo
orA
ctiv
ePa
ssiv
eH
alf
Full
Lin
kbl
ocka
geB
ackh
aul
issu
esL
owH
igh
Res
ults
/per
form
ance
Con
giu
etal
.[1
01]
Yes
No
Yes
No
Yes
No
Yes
No
Yes
No
Rel
aylin
kpe
rfor
med
bette
rfo
rhi
ghda
tara
tetr
affic
envi
ronm
ent.
G.W
ahab
etal
.[1
04]
Yes
No
No
Yes
No
No
Yes
No
No
Yes
Ext
end
the
cove
rage
inN
LO
Sha
ving
gain
of20
dB.
Bis
was
etal
.[1
05]
Yes
No
Yes
No
Yes
No
Yes
No
No
No
Impr
ovin
gth
ene
twor
kca
paci
tyan
din
crea
sed
inco
vera
gear
ea.
Zhe
nget
al.
[106
]Y
esN
oY
esN
oY
esN
oY
esN
oY
esN
oO
ptim
alre
lay
sele
ctio
nre
sulti
ngbe
tter
conn
ectiv
ityW
eiet
al.
[108
]N
oY
esY
esN
oY
esN
oN
oY
esY
esN
oR
educ
eth
ehi
ghpa
thlo
ssan
dov
erco
me
link
bloc
kage
Shao
oet
al.
[109
]N
oY
esY
esN
oY
esN
oN
oY
esN
oY
esT
hetr
affic
load
and
qual
ityof
link
was
adde
dto
max
imiz
eth
epe
rfor
man
ceof
netw
ork
Yan
get
al.
[110
]N
oY
esY
esN
oY
esN
oY
esN
oY
esN
oE
xten
sion
inco
vera
gear
eaw
ithbe
tter
end
toen
dpe
rfor
man
ce.
Kw
onet
al.
[111
]N
oY
esY
esN
oY
esN
oY
esN
oY
esN
oO
ptim
alre
lay
sele
ctio
nby
geom
etri
can
alys
isto
impr
ove
the
end
toen
dco
nnec
tivity
Alk
awtr
aet
al.
[114
]Y
esN
oY
esN
oN
oN
oY
esN
oN
oY
esR
educ
eth
enu
mbe
rof
rela
yno
des
and
max
imiz
eth
een
dus
erpe
rfor
man
ce.
Shah
etal
.[1
15]
Yes
No
Yes
No
Yes
No
Yes
No
No
Yes
Bet
ter
perf
orm
ance
achi
eved
inre
liabi
lity,
cove
rage
and
capa
city
.M
arco
etal
.[1
16]
Yes
Yes
Yes
No
No
Yes
Yes
No
Yes
No
The
thro
ughp
utw
asin
crea
sed
byut
iliza
tion
the
licen
sed
asw
ell
asun
licen
sed
freq
uenc
yba
nd.
RN
Room in a building
Optical
fiber
HeNB
UE
Other room in same building
RN
RN RN
Fig. 10. Mm-wave relaying for indoor communication
in the selection of the RN as well as during the actual transferringof the information between the connecting nodes.
6.4. Security issues Security is an important challengefor the reliability of cooperative communication. There are anumber of security threads in the cooperative network whereinfake node acts as a reliable node by presenting its full availabilityand better channel condition to attract the other nodes in thenetwork for the purpose of acquiring the information. In future,a strong secure mechanism is required in the cooperative networkfor reliable and complete security loops in the network for effectivecommunication.
6.5. Optimal location and cost-effectiveness In acooperative network, the optimal location of the selected RNhas a greater impact on the end to end performance. Thedifferent challenges faced by mm-wave can be overwhelmedby relaying nodes, however, an increase in a number of RNs affectthe implementation cost. In future studies, a proper mechanismis needed to sort out the deployment of a RN in the optimallocation especially in the mm-wave relaying technique for cost-effectiveness and a better performance.
7. Conclusion
Cooperative communication is a promising technique that con-tributes to achieving high data rates in the next-generation wirelessnetworks. Cooperative communication can possibly overcome dif-ferent challenges faced by wireless channels and enhance the num-ber of significant factors i.e. spectral efficiency, coverage in theshadow area, utilization energy efficiently etc. for a better perfor-mance. However, the challenging task of cooperative communi-cation is to find out the best and optimal RN between all otherexisting RNs, which essentially affects the overall performanceof the network. In this study, we discussed the different meth-ods and criteria for selection of the best RN generally basedon different communication performance metrics i.e., SNR, CSI,BER, and PER etc. and analyzed how appropriate selection affectsthe performance. Moreover, the factor of reliability is discussedthat is essential to be considered during the selection processof a RN in cooperative communication because of the securitythreads that are highly vulnerable to malicious attack in the net-work. In the next-generation wireless network, mm-wave has ahuge and potential frequency band available to fulfill the demandof a high data rate, however, different challenges seem to make itmore difficult. In this article, we also focused that how cooperativecommunication can be used to overcome those challenges facedby mm-wave efficiently and found that it has the ability to generatebetter outcomes. However, there are many future challenges thatneed to be addressed i.e., Interference management, power con-summation, carrier aggregation, security issues etc. for fulfillingthe demands of next-generation wireless networks.
665 IEEJ Trans 14: 658–669 (2019)
M. ASSHAD ET AL.
Acknowledgments
This study was supported by the Kocaeli University Scientific ResearchUnit (Project number: 2017/061). We are also thankful to the anonymousreviewers for their useful suggestions.
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Muhammad Asshad (Non-member) received his B.S. degree inComputer Science from Hazara UniversityMansehra and M.S. degree in Telecommuni-cation & Computer Network from Iqra Uni-versity Islamabad. He is currently a Ph.D.scholar at the department of Computer Engi-neering at Kocaeli University Turkey. Hiscurrent research areas including performanceanalysis, relaying diversity schemes, cooper-
ative network and wireless fading channels.
Sajjad Ahmad Khan (Non-member) received his B.S. degree inComputer Science from UET Peshawar andMS degree in Telecommunication & Com-puter Network from Islamabad, Pakistan.Currently, he is a Ph.D. scholar in the depart-ment of Computer Engineering at KocaeliUniversity, Turkey. He is currently work-ing in wireless Heterogeneous Networks(HetNet). His research areas include Radio
Resource Management (RRM) and interference management inLTE Femtocell Networks.
668 IEEJ Trans 14: 658–669 (2019)
COOPERATIVE COMMUNICATIONS FOR NEXT-GENERATION WIRELESS NETWORKS
Adnan Kavak (Non-member) is currently a Professor in Depart-ment of Computer Engineering at KocaeliUniversity, Kocaeli, Turkey. He received hisM.S., and Ph.D. degrees from the Com-puter Engineering Department at Universityof Texas-Austin. He was a senior researcherat wireless system lab to Samsung Telecom-munication in Dallas, TX between 2000 and2001. He was also a visiting Professor at the
University of Texas at Austin in 2008–2009. His recent researchareas are Wireless Communication, Intelligent Antenna and MIMOSystems, Cloud Computing (Signaling and Synchronization), E-Health Systems, Data Mining Applications, and Decision SupportSystems.
Kerem Kucuk (Non-member) is an Associate Professor in Depart-ment of Computer Engineering at KocaeliUniversity, Kocaeli, Turkey. He receivedhis B.S., M.S., and Ph.D. degrees from theElectronics and Computer Education Depart-ment at Kocaeli University. He was alsoa guest researcher and a visiting scholarat Twente University, Pervasive SystemsGroup, Twente, Netherlands, and the Wire-
less Information Systems Laboratory, the University of Texas atDallas, TX. He is currently interested in the internet of things,vehicular networks, computer and wireless networks, ultrawide-band systems, embedded systems, and real-time signal processing.
Dawson Ladislaus Msongaleli (Non-member) received his B.S.degree in Computer Science. He was withSakarya University, Turkey, pursuing M.Sc.in Computer and Information Engineering.Currently, he is with the Department ofComputer Engineering of Kocaeli Univer-sity, Turkey, undertaking Ph.D. in Com-puter Engineering. His research interestsinclude optic-fiber networks, optic wireless
