Device‐to‐device communications using EMTR technique
2017; Institution of Engineering and Technology; Volume: 12; Issue: 3 Linguagem: Inglês
10.1049/iet-spr.2016.0581
ISSN1751-9683
AutoresSiavash Rajabi, Seyed Ali Ghorashi, Vahid Shah‐Mansouri, Hamidreza Karami,
Tópico(s)Millimeter-Wave Propagation and Modeling
ResumoIET Signal ProcessingVolume 12, Issue 3 p. 320-326 Research ArticleFree Access Device-to-device communications using EMTR technique Siavash Rajabi, Siavash Rajabi Cognitive Telecommunication Research Group, Faculty of Electrical Engineering, Shahid Beheshti University G. C., 1983963113 Tehran, IranSearch for more papers by this authorSeyed Ali Ghorashi, Corresponding Author Seyed Ali Ghorashi a_ghorashi@sbu.ac.ir Cognitive Telecommunication Research Group, Faculty of Electrical Engineering, Shahid Beheshti University G. C., 1983963113 Tehran, Iran Cyberspace Research Institute, Shahid Beheshti University G. C., 1983963113 Tehran, IranSearch for more papers by this authorVahid Shah-Mansouri, Vahid Shah-Mansouri School of Electrical and Computer Engineering, University of Tehran, Tehran, IranSearch for more papers by this authorHamidreza Karami, Hamidreza Karami Department of Electrical Engineering, Bu-Ali Sina University, Hamedan, IranSearch for more papers by this author Siavash Rajabi, Siavash Rajabi Cognitive Telecommunication Research Group, Faculty of Electrical Engineering, Shahid Beheshti University G. C., 1983963113 Tehran, IranSearch for more papers by this authorSeyed Ali Ghorashi, Corresponding Author Seyed Ali Ghorashi a_ghorashi@sbu.ac.ir Cognitive Telecommunication Research Group, Faculty of Electrical Engineering, Shahid Beheshti University G. C., 1983963113 Tehran, Iran Cyberspace Research Institute, Shahid Beheshti University G. C., 1983963113 Tehran, IranSearch for more papers by this authorVahid Shah-Mansouri, Vahid Shah-Mansouri School of Electrical and Computer Engineering, University of Tehran, Tehran, IranSearch for more papers by this authorHamidreza Karami, Hamidreza Karami Department of Electrical Engineering, Bu-Ali Sina University, Hamedan, IranSearch for more papers by this author First published: 01 May 2018 https://doi.org/10.1049/iet-spr.2016.0581Citations: 5AboutSectionsPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Abstract Device-to-device (D2D) communication is a promising 5G technology, which helps to increase spectrum efficiency and sum-rate, as well as to decrease experienced latency. The main challenges of D2D communication are power consumption of paired devices, channel estimation between device pairs, and interference management between devices that use the same time and frequency resources. The electromagnetic time reversal (EMTR) technique is used in D2D communications to focus the signal power in both time and space domains for power efficiency of end users, to simplify the structure of transceivers, to help channel estimation in a low complexity way, and to nullify the effect of interference. First, in the time domain, the effect of using EMTR technique is investigated and its performance is compared with a similar non-EMTR system. Then, EMTR technique is used in an OFDM-based system and its advantages in the context of signal to interference plus noise ratio (SINR) and sum-rate are presented analytically and through computer simulations. Simulation results show a significant gain in SINR, sum-rate and received signal power for the proposed EMTR-based D2D system. 1 Introduction Device-to-device (D2D) communication is a proximity-based technology that enables two nearby devices to communicate directly, without the aid of evolved node base (eNB) station. The main advantages of this technology are low latency, new peer to peer and location-based services and better overall throughput of the network [1]. D2D communication as a new standardised service for LTE-A networks is a promising candidate which can be used along with millimetre-wave communication for heterogeneous 5G cellular networks [1, 2]. However, the main concerns about this new technology are energy consumption as well as the mutual interference between D2D and cellular users that use the same network resources [3]. Electromagnetic time reversal (EMTR) is a technique for focusing the waves in space and time domains and is based on two phases of sending and receiving electromagnetic waves between the transmitter and receiver. This technique was first introduced for acoustic waves [4] and then, it has received a lot of attention in other areas. In [4], the time reversal of ultrasonic fields was presented as a way of focusing ultrasonic energy onto a target. More recently, the technique has also been used in electromagnetics [5] and is applied to object imaging and detection [6]. The history of using EMTR technique for radio wave communications dates back to early 2000s. Due to its ability to reduce power consumption (that was reported as the spatial-temporal focusing effect) and the ability to simplify the structure of transceivers, it has been used widely in [7-21]. In [7], several metrics are proposed to show space–time focus property of EMTR technique for single input single output systems in two different scattering environments. In [8], measurements and mathematical analysis have been used to investigate multiple input single output (MISO) multiuser downlink system in terms of bit error rate (BER) and focusing capability. Some other works [9-11] focus on how to mitigate the effect of inter symbol interference (ISI) in EMTR-based systems. Kyritsi et al. [9] have used the zero forcing (ZF) and minimum mean-square error pre-equalisation techniques for ISI reduction and an equalised spatial multiplexing EMTR scheme is presented in [10]. Taking into account the limitations of similar works, the authors of [11] proposed a ZF pre-equaliser for EMTR systems in an indoor environment. A few papers have investigated EMTR technique in OFDM-based systems [12, 13]. The authors of [12] investigate EMTR-OFDM system in the context of cyclic prefix (CP) length due to the extension of channel length in EMTR technique. They show that it is possible to keep the size of CP constant using EMTR technique. In [13], the performance of an MISO OFDM system without interference has been compared with the maximum ratio combining (MRC) and equal gain combining methods in terms of BER, bit-rate and achievable diversity. The authors in [14-19] have worked on a multiuser downlink system named time-reversal division multiple access (TRDMA). First, they introduced EMTR as a green wireless communication paradigm in [14]. Next, by improving the structure of their first paper, they introduced an MISO downlink multiuser system, named TRDMA in [15] and compared this method with a nearly similar RAKE receiver. The main drawback of TRDMA is ISI in receiver. Therefore, in [16], they proposed a water filling method as a waveform design to solve ISI problem in TRDMA. In [17], they compared a 100 MHz TRDMA system using the proposed waveform in [16] with an OFDM-based system with 20 MHz bandwidth. Then, they used TRDMA as a solution for the next generation Internet-of-things networks [18]. Recently, they have proposed their system as a new solution for 5G cellular networks [19]. Furthermore, there are some works in [8, 14, 20, 21] that have investigated this technique experimentally. The authors in [20] proposed an EMTR system architecture based on experimental results. Major issues associated with implementation of time reversal, such as sampling, quantisation, truncation length and interpolation, are discussed. In [21], an EMTR radio prototype was built to conduct EMTR research and development. This EMTR prototype is a customised software-defined radio platform for designing and deploying EMTR-based communication systems. Most of the works that use EMTR technique for radio wave communications, consider MISO multiuser downlink systems. To the best of our knowledge, no work has been done in the field of D2D communications, using EMTR technique, which takes into account mutual interference and power consumption of two nearby devices. The main purpose of this paper is to investigate the effect of pure EMTR technique on the performance of a D2D enabled wireless communication system. With pure, we mean that no pre-equalisation, no channel estimation or any other techniques are used in our system model. We named the related works in the literature that did not use the EMTR technique and have similar system model to our proposed system model as non-EMTR-based systems [22]. In this paper, it is shown that EMTR has important advantages that are completely matched with common challenges of D2D communications; (a) Reducing power consumption: use of pulse shaping for channel impulse response at the transmitter, leads to a decrease in the consumption power of transmitters. This pulse shaping mechanism makes the transceiver structure very simple. (b) Changing the destructive effect of multipath environment to a constructive effect: increasing the number of propagation paths in a wireless channel, degrades the signal to interference plus noise ratio (SINR) in an ordinary system. However, the spatial-temporal focusing effect of EMTR technique stands against of severe effect of ISI and inter user interference (IUI) in the receiver. (c) Nullifying mutual interference: this means that using a matched filter structure at the transmitter side with the aid of delta like pulse transmission at the receiver, makes mutual interference between co-channel users, ineffective. This feature is important in environments with many co-channel D2D and cellular UEs and leads to a green wireless communication system design. (d) Self-channel estimation between two paired D2D connections: by using two round trip phases of EMTR technique, there is no need to channel estimation and therefore, pilot symbols can be used for data transmission. This paper is divided into two parts. First, the structure of EMTR transceiver is introduced for an arbitrary D2D communication system in time domain, and SINR and sum rate of the proposed system are compared with a similar non-EMTR-based transceiver. Next, due to the importance of OFDM-based transceivers in next generation wireless networks SINR of an OFDM-EMTR-based transceiver is compared with that of an ordinary OFDM system in the frequency domain. This paper is organised as follows: In Section 2, the system model and the process of communications and mathematical theory of EMTR-based transceivers are introduced. In Section 3, a D2D communication system using EMTR technique is compared theoretically with an ordinary D2D communication system in time domain, by using metrics such as power consumption, received SINR, and sum-rate. In Section 4, an OFDM-EMTR-based transceiver is compared with an ordinary OFDM system in frequency domain. Section 5 presents the simulation results of the proposed EMTR-based D2D mode communication with non-EMTR methods and these results are compared with mathematical formulation that are derived in Sections 3 and 4. Finally, Section 6 concludes the paper. 2 System model Consider two pairs of devices with co-channel D2D connections, located at the proximity of each other as shown in Fig. 1. The goal is to show the impact of using EMTR technique in the context of D2D communications. Generalising the system model to more than two D2D connections and cellular links is straight forward. As shown in Fig. 1, there are two types of channels in this scenario; and are direct channels between paired D2D users and and are interference channels between a transmitter and the other proximity co-channel receivers. Multipath Rayleigh slow fading channel is assumed between different devices with the impulse response of (1)where and are complex amplitude and propagation delay of the tap of the channel impulse response, respectively [23]. For the sake of simplicity and without loose of generality, this impulse response can be considered as a discrete time signal h [n] with length L, where . It is also assumed that channel impulse response taps are zero mean circular symmetric complex Gaussian (CSCG) random variables. Fig. 1Open in figure viewerPowerPoint Two co-channel D2D connections (A–B and C–D). Users A and C are transmitters and users B and D are receivers. Solid lines are direct links and dashed lines are interferer links EMTR-based communication consists of two phases: first, the receiver sends an impulse-like pulse to the transmitter. Based on the time reciprocal characteristic of wireless multipath channel, the received pulse at the transmitter is nearly the impulse response of the channel between the transmitter and receiver. A complete proof of EMTR technique, using Maxwell's equations can be found in [24, 25]. Then, the transmitter uses the normalised time reversed and conjugate of the received and recorded pulse at phase one, as a pulse shaper filter at the final stage of the system. Then, it sends its symbols using this filter to the receiver. The impulse response of the EMTR filter can be expressed as (2)where denominator is used for normalisation to be comparable with non-EMTR systems. This technique can be implemented independently from the transceiver structure with arbitrary coding and modulation schemes. It means that in a heterogeneous 5G system, proximity D2D connections, independent of communication protocols in the network can use this technique for their proximity, power effective services. Furthermore, each D2D UE must have an option to connect to the network using eNB, too. Therefore, there should be a mechanism for mode selection between cellular and D2D schemes. The existing approaches for decision making between cellular and D2D modes are divided into several categories such as distance-based methods [26], minimising the energy or power consumptions [27] and maximising network sum rate [28]. In this work, we assume a distance-based mode selection in which the decision between D2D and cellular modes is made based on the UE's distance from eNB and each others. It means that if the distance between potential D2D pairs is less than the minimum distance of each of them to the eNB, then, D2D mode is selected. Otherwise the cellular mode is selected. In the following, D2D communication system using EMTR technique is investigated in time domain. 3 EMTR D2D communications in time domain In this section, we investigate the EMTR-based transceiver structure (Fig. 2) for D2D users of the system model in Fig. 1. Assume that transmitters (A and C in Fig. 1) send a sequence of modulated symbols ( and , respectively). Then, the received symbols in B can be expressed as (3)where and are the impulse responses of EMTR filters that are used in A and C, respectively. These impulse responses are generated after the first phase of EMTR technique where the receivers B and D send impulse-like pulses to the transmitters A and C, respectively and using (2), these impulse responses are generated. The received signal in (3) consists of three parts: (i) the desired signal which is the sample of the EMTR filter and wireless channel impulse response convolution, (ii) ISI due to the EMTR filter extension, (iii) interference from co-channel near located D2D connection C –D and (iv) zero mean complex Gaussian noise Z [k] with variance . It is assumed that phase and delay compensations in the transmitter and receiver have been done successfully [12, 13]. The received signal power then can be expressed as the expectation over channel taps and transmitted symbols (4) Fig. 2Open in figure viewerPowerPoint EMTR-based communication system Channel taps and transmitted symbols are independent. is the power of transmitted symbols . Therefore, the expectations over them can be separated. The third equality follows from convolution of EMTR pre-filter and channel impulse response as (5)If no arrangement is done to compensate ISI, in a continuous stream of data, the power of ISI can be expressed as (6)Finally, the IUI power is (7)Therefore, the received SINR at B can be expressed as (8)If EMTR technique is not employed, the received symbol at time k can be expressed as (9)In this case, the received power of signal, ISI and IUI can be expressed as (10) (11)and (12)Therefore, the received SINR of a non-EMTR-based system at the receiver can be expressed as (13)If exponential power delay profile for CSCG taps of channel impulse response is assumed [29], the variance and forth moment are obtained as follows [15, 30] (14) (15)It should be noted that the choice of exponential power delay profile is because of its tractability mathematically. Therefore, the simulation and theoretical results can be compared fairly. Furthermore, this model is considered in the literature numerously [8, 11, 14, 15]. Then, the expectation of signal, ISI and IUI powers in (4), (6) and (7) for EMTR-based system in time domain can be expressed as (16) (17)and (18)While for non-EMTR-based system, we have (19)and (20)These analytical simplifications in (16)–(20) will be used in Section 5 to compare simulation and analytical results of this section. 4 EMTR-OFDM D2D communications In this section, EMTR technique is used in an OFDM-based transceiver. In this paper, we assume that the channel between the transmitter and the receiver is quasi static [31]. It means, after this pre-defined transmission period, a delta like pulse negotiation between the transmitter and receiver is necessary. The proposed system is the same as in Fig. 2 except that Tx and Rx use OFDM technique. Considering the A –B connection of Fig. 1, the received signal at B after two aforementioned phases of EMTR technique (Section 3) with transmitter A can be expressed as (21)If the normal OFDM receiver is considered without EMTR filter, the received signal can be expressed as (22)where and are the powers of transmitted symbols at A and C, respectively. and are the distances between A to B and C to B, respectively, and is the path loss exponent of desired channel. , and are fast Fourier transforms (FFTs) of the impulse response of channels , and , respectively, at the subcarrier. and are the transmitted symbols from user A and C and Z [n] is additive white Gaussian noise (AWGN) of the channel with the variance . and are the normalisation factors due to the normalised EMTR filters in (2) and can be expressed as (23)and (24)where N is the number of subcarriers that are used in FFT. In (21), the received signal consists of three parts; the desired signal from A that is paired with B in a D2D connection, the interference signal from co-channel proximity located user C, and the AWGN noise. According to (21), the SINR of user B can be expressed as (25)In non-EMTR-OFDM-based system, due to (22), the SINR at user B can be expressed as (26)The difference between the values of (25) and (26) is presented in the next section. 5 Simulation results In this section, some metrics for D2D communication performance such as SNR, SINR and sum-rate are compared for EMTR and non-EMTR-based systems. It should be noted that as opposed in [7, 8, 11], the EMTR technique effects depend on the propagation channel, significantly. It means that with the change of wireless channel model, different results may be produced. The results of this section are due to the parameters that are listed in Table 1 and theoretical models that are investigated in Sections 3 and 4. Table 1. Simulation parameters Parameter Value bandwidth, BW 20 MHz 2048 23 dBm 50 ns 125 L 20–200 −174 dBm/Hz iterations 10,000 3 In Fig. 3, the received SINR and power of EMTR and non-EMTR-based communication UEs are compared as a function of the number of channel multipath components. In Fig. 3 a, solid curves are analytical SINRs that are obtained via (16)–(20), while dashed curves are SINRs that are computed via simulation with Table 1 parameters. The figure shows an accurate accordance of analytical and simulation results. The results show that the SINR of EMTR-based UEs does not change for different number of paths. The main reason of this constant behaviour is that by increasing the number of channel taps in EMTR-based system, the effect of ISI and IUI increases in accordance with the increase of received spatial-time focused power. However, for non-EMTR-based UEs, a significant decrease in received SINR is achieved by increasing the number of channel taps. Fig. 3Open in figure viewerPowerPoint Effect of EMTR technique on received SINR and power (a) SINR as a function of number of paths between Tx and Rx (L), (b) Received power as a function of number of paths between Tx and Rx (L) There is a remarkable (12–20 dB) improvement in SINR for EMTR-based UEs. Notice that the EMTR-based receiver simulation results here do not include any equalisation (like in [9-11]) and channel estimation. If these techniques were used, the improvement could be much more. In Fig. 3 b, the ratio of (obtained in (4)) in EMTR to (obtained in (10)) in non-EMTR-based communication UEs is compared for different number of channel taps. The results show how EMTR technique changes the destructive effect of multipath channel to a constructive one. The power consumption of EMTR starts from 13 dB for 20 channel taps to 20 dB in 200 channel taps. In Fig. 4, the SINR of EMTR and non-EMTR-based systems are compared as a function of SNR for two channel models. SNR is defined as the average received signal power normalised by noise power and is formulated as (27) Fig. 4Open in figure viewerPowerPoint SINR of EMTR-based and non-EMTR-based systems as a function of effective SNR for two different channel models (a) Exponential channel model, (b) Indoor UWB channel model The exponential channel model has been used in Fig. 4 a. The results are for a multipath channel with 200 taps. A 20 dB gain for EMTR-based system is shown in this result, when compared with non-EMTR one. The SINR curves increase linearly in the range of −20 to 0 dB. To investigate the effects of EMTR-based system in an indoor ultra wideband (UWB) wireless communication channel, the SINR of EMTR and non-EMTR-based systems are compared as a function of SNR in an SG3a UWB multipath channel model in Fig. 4 b. The result shows that the power focusing effect of EMTR-based method increases in UWB multipath channels when compared with Fig. 4 a. In other words, the higher delayed echoes in this type of channel becomes an advantage for the EMTR-based systems. Fig. 5 compares sum-rate of EMTR and non-EMTR systems with each other. Sum-rate is considered as the sum of ergodic link spectral efficiency of users of Fig. 1 as (28) Fig. 5Open in figure viewerPowerPoint Sum-rate of EMTR-based and non-EMTR-based systems as a function of effective SNR Due to the spatial-temporal focusing property of EMTR technique, especially in −10 to 10 dB of SNRs range, there is a linear increase in sum-rate of EMTR system, whereas in non-EMTR system due to the severe effects of ISI and IUI, without any increase in intended received signal, there is an inconsiderable increase in sum-rate. In Fig. 6, we investigate the effect of EMTR on multi co-channel D2D connections. Similar to Fig. 4, results show a meaningful difference between EMTR and non-EMTR-based methods. However, it should be noted that the difference between the two methods does not increase with the number of D2D pairs. The main reason is that the IUI part in SINR increases linearly with the increase of D2D connections in both EMTR and non-EMTR systems. In this paper, we aim to investigate the effect of pure EMTR technique (without any pre-equalisation or other techniques) on the SINR of two co-channel D2D connections. This is consistent with the results of [11, 15] that considered EMTR technique in multi user systems. In some other related works, simplification assumptions have used which have decreased the effect of IUI term [8, 14]. Fig. 6Open in figure viewerPowerPoint SINR of EMTR-based and non-EMTR-based systems as a function of the number of co-channel D2D connections In the following, the SINR of EMTR-OFDM-based system is compared with a normal OFDM system in the system model of Fig. 1. In Fig. 7, the SINR for EMTR and non-EMTR methods are compared as a function of the ratio of mean interference link distance (i.e. mean distance between C and B, ) to mean direct link distance (i.e. mean distance between A and B, ). In this figure, and changes from 10 to 90 m. The results show nearly 10 dB gain in SINR for EMTR-based system and it is because of spatial focusing and time compressing of received signal in EMTR method. Fig. 7Open in figure viewerPowerPoint SINR of EMTR-OFDM and ordinary OFDM systems as a function of ratio of interferer to direct link Finally, Fig. 8 shows the effect of spatial focusing and time compression of EMTR on two co-channel D2D connections in proximity of each other in Fig. 1 in a real multipath scattering environment. To simulate EMTR signals, a finite difference time-domain (FDTD) method-based solver is used. In the FDTD method, the type of the excitation waveform can impress the impulse response results. A source waveform should be chosen such that its frequency spectrum includes all the frequencies of the interest for simulation or experiment. It should have a smooth turn-on and turn-off to minimise the undesired effects of high-frequency components. To the best of our knowledge, Gaussian pulse or cosine-modulated Gaussian pulse are the best candidate to obtain the EMTR results in time domain [32]. In this example, the excitation pulse is a modulated Gaussian wave as follows: (29)where is the modulation frequency of the Gaussian pulse. The value of is taken as , where denotes the bandwidth of the Gaussian pulse. The computational domain is a site. To truncate the computational domain in the FDTD solver, a perfectly matched layer is set on the four lateral surfaces, as well as on the top surface of the structure. The result obtained by FDTD solver after using EMTR is shown in Fig. 8. This figure shows a spatial and temporal focusing after reversing the receiving signal and back propagation process. As shown in Fig. 8, the EMTR can be used to reduce the interference at the receiver antenna location (D in this figure). Fig. 8Open in figure viewerPowerPoint Effect of spatial-temporal focusing property in scattering environment 6 Conclusion The main idea of this paper is to show the use of EMTR technique and its advantages in D2D communications in a heterogeneous cellular network. The main advantages are lower power consumption, simpler structure of receiver, mitigating the harmful effect of interference with focusing the propagation power in terms of time and space and changing the destructive effect of dense scatterer environment to a constructive effect. The analytical investigation and simulation results are about the effect of EMTR system in comparison with non-EMTR ones, as well as showing the use of this technique and its effects in an OFDM-based system in frequency domain. Metrics such as power consumption, SINR and sum-rate are compared for EMTR and non-EMTR-based systems in time domain and for OFDM systems in frequency domain. The results show a considerable gain in power, SINR and sum-rate for EMTR-based system. In this paper, we investigated the effect of pure EMTR technique on the SINR of two co-channel D2D connections. Some other techniques such as pre-equalisation and using multi-element antenna systems can be considered in the transmitter to mitigate the effects of ISI and IUI for future works. 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