- Open Access
Analyzing the potential of full duplex in 5G ultra-dense small cell networks
© The Author(s) 2016
- Received: 29 June 2016
- Accepted: 26 November 2016
- Published: 13 December 2016
Full-duplex technology has become an attractive solution for future 5th generation (5G) systems for accommodating the exponentially growing mobile traffic demand. Full duplex allows a node to transmit and receive simultaneously in the same frequency band, thus, theoretically, doubling the system throughput over conventional half-duplex systems. A key limitation in building a feasible full-duplex node is the self-interference, i.e., the interference generated by the transmitted signal to the desired signal received on the same node. This constraint has been overcome given the recent advances in the self-interference cancellation technology. However, there are other limitations in achieving the theoretical full-duplex gain: residual self-interference, traffic constraints, and inter-cell and intra-cell interference. The contribution of this article is twofold. Firstly, achievable levels of self-interference cancellation are demonstrated using our own developed test bed. Secondly, a detailed evaluation of full-duplex communication in 5G ultra-dense small cell networks via system level simulations is provided. The results are presented in terms of throughput and delay. Two types of full duplex are studied: when both the station and the user equipments are full duplex capable and when only the base station is able to exploit simultaneous transmission and reception. The impact of the traffic profile and the inter-cell and intra-cell interferences is addressed, individually and jointly. Results show that the increased interference that simultaneous transmission and reception causes is one of the main limiting factors in achieving the promised full-duplex throughput gain, while large traffic asymmetries between downlink and uplink further compromise such gain.
- Full duplex
- Small cell
- Traffic profile
Wireless communication is stimulating a networked society, where data is exchanged anytime, everywhere, between everyone, and everything. In 2000, only 10 GB of mobile data traffic was reached per month, whereas in 2015 such amount represented 3.7 billions of gigabytes . This enormous traffic increase was generated by several causes: the introduction of new services and applications, the massive use of social networks, and the utilization of smart devices with mobile data connection, such as smartphones and phablets, among others. The amount of carried data will continue to grow, and it is expected to be eightfold in 2020, with reference to 2015. A new 5th generation (5G) radio access technology is expected to accommodate the exponentially growing demand of mobile traffic. Several strategies may be considered for boosting capacity, such as cell densification or multiple-input multiple-output (MIMO) technology with a large number of antennas. Recent advances in transceiver design have also attracted the attention of the research community on full-duplex (FD) technology. FD allows a device to transmit and receive simultaneously in the same frequency band, thus, theoretically, doubling the throughput over traditional half-duplex (HD) systems. Given the capabilities of this technology, it is considered as a potential candidate for future 5G systems.
A 5G concept tailored for small cells was proposed in , optimized for dense local area deployments. The system assumes the usage of 4×4 MIMO transceivers and receivers with interference suppression capabilities. Though originally designed as a HD time division duplex (TDD) system, the proposed concept can easily support FD communication. In order to have an operational FD node, the self-interference (SI), i.e., the interference caused by the transmit antenna to the receive antenna located in the same device should be attenuated as much as possible, ideally below the receiver noise power level. Several techniques were proposed to provide high levels of self-interference cancellation (SIC) [3–7]. In , a detailed study of the passive SIC for FD infrastructure nodes is presented. Several techniques are analyzed, individually and jointly, and then evaluated experimentally. The authors argue that the main problem in SIC are the reflections or multi-path, while the direct link is easier to cancel. The former requires active suppression while the latter is tackled with passive cancellation. For this reason, the authors recommend to apply both active and passive cancellations whenever possible. Finally, the experimental results show that the most appropriate approach is to combine directional antennas with cross-polarization and an absorber. Recent results show that SI can be reduced of around 100 dB [6, 8]. This may suffice for considering FD a realistic option, at least according to transmit power constraints.
The promised FD throughput gain may be compromised by several limitations. First, the residual SI may still negatively affect the reception of the desired signals. In addition, the increased interference caused by FD and the traffic profile may further compromise such theoretical FD gain. FD doubles the amount of interfering streams, leading to an increased inter-cell interference (ICI). Furthermore, exploiting FD is only possible when there is data traffic in both link directions, uplink (UL) and downlink (DL).
There are three kinds of FD applications. The first is the relay FD, where the base station (BS) is FD capable and relays data from HD user equipments (UEs). Relay FD is thoroughly analyzed in  for two use cases, amplify-and-forward (AF) and decode-and-forward (DF). The available self-interference cancellation techniques are also intensively described. An interesting outcome of  is that the biggest beneficiaries of FD might be the networks that have short communication range and low transmit power, such as small cells. Furthermore, in , the impact of non-ideal SIC on the end-to-end network capacity is analyzed in the context of FD relaying. The authors propose a power allocation scheme to reduce the SI. The results show gains close to the theoretical double throughput. However, the authors do not consider either the impact of inter-cell interference or the traffic profile. The work presented in this article focuses on the other two types of FD: the case where both the BS and the UE are FD capable, namely bidirectional FD, and the BS FD configuration, which refers to the situation where only the BS is able to exploit simultaneous transmission and reception with HD users. Consequently, the literature presented next will focus on these two cases.
A novel design of a FD MIMO radio is presented in . The authors’ proposal provides meaningful results on SIC, reducing the complexity, cost and error of current models. However, the evaluation of the FD gain is extracted under unrealistic conditions, i.e., without considering the impact of the inter-cell interference and the traffic profile.
A number of studies analyzes the FD performance in small cell scenarios [12–18] and in a macro cell network  based on interference levels, disregarding the type of traffic in the network. In , the gain that FD provides compared to HD, assuming ideal SIC, is analyzed from a signal-to-interference-plus-noise ratio (SINR) perspective. The authors conclude that the FD gain is below the promised 100%. The authors in [13, 14] study the achievable bit rate depending on different residual SIC levels and interference conditions. Both works analyze the SINR region where FD outperforms HD, concluding that in highly interfered scenarios, switching between FD and HD provides the optimal results. In , the FD throughput performance using different types of receivers and ideal SIC in a multi-cell scenario is studied. Results show an average throughput gain of 30–40%. In , results comparing MIMO HD and FD are presented, assuming full buffer traffic. The authors conclude that, without interference, FD can provide up to 31 and 36% gain in terms of throughput and delay, respectively, while in case of interfered scenarios, HD may outperform FD due to MIMO spatial multiplexing gains. Tong and Haenggi  focus on an ALOHA system to provide analytical expression to optimize the capacity given the density of FD and HD nodes. The region where FD outperforms HD is studied, under the assumption of non-ideal SIC, but without considering the impact of the traffic profile. The authors conclude that achieving the double throughput gain is not possible, and the FD gain depends on the level of SIC. The impact of user-to-user or intra-cell interference is studied in . The authors demonstrate via simulation results that setting a different transmit power for the BS and UE has a positive impact on the network performance, even under residual SI. A power control algorithm to maximize the sum rate of DL and UL via an efficient switching between HD and FD is proposed in . The authors show that there is a SINR region where HD outperforms FD.
The impact of the traffic type is addressed in the studies [6, 8, 20–23]. Goyal et al.  propose a hybrid FD/HD scheduler that selects the mode that maximizes the network throughput. The evaluation is carried out considering asymmetric traffic, showing that FD always outperforms HD. However, a strong isolation between the cells is assumed, which may downgrade the ICI impact. Malik et al. propose a power control algorithm to accommodate asymmetric traffic . The proposed scheme, evaluated in a single cell scenario, shows an improvement in DL at the expense of lowering the UL rate. Mahmood et al.  study the impact of symmetric and asymmetric traffic in a multi-cell scenario. Throughput results show that the FD gain reduces with the perceived ICI and the traffic ratio. Heino et al.  conclude that in dense deployment of small cells, where transmit powers are low and distances among nodes are short, 100 dB of SIC is sufficient to consider ICI as the main limiting factor for achieving the promised FD gain. Moreover, they remark that large asymmetric traffic ratios between DL and UL data may compromise the usage of FD and hence its gain. These challenges are also described in [8, 23].
The above-mentioned works study the performance of FD assuming User Data Protocol (UDP) traffic. However, most of the Internet traffic is carried over Transport Control Protocol (TCP) flows, with a small percentage of UDP flows . TCP  is used to provide a reliable communication and reduce packet losses. Its congestion control mechanism limits the amount of data that can be pushed into the network, based on the reception of positive acknowledgments (ACKs) . This procedure causes an increase in the delay and a reduction of the system throughput. FD may mitigate such drawbacks since it may allow to accelerate the TCP congestion control mechanism, given the possibility of transmitting and receiving simultaneously. It is important to notice that the previously mentioned works disregard the usage of features such as link adaptation and recovery and congestion control mechanisms.
In this paper, we perform a system level evaluation of the full-duplex performance in dense small cells, where the impact of the traffic profile and the inter-cell and intra-cell interferences is addressed, individually and jointly. The study is carried using a system level simulator which implements both the lower and the upper layers of the Open Systems Interconnection (OSI) model and features mechanisms such as link adaptation and recovery and congestion control mechanisms. The contribution of this paper is twofold. Firstly, achievable levels of SIC are demonstrated using our own developed test bed. Secondly, a detailed evaluation of FD communication in 5G ultra-dense small cell networks is provided. Two types of FD communication are studied: BS FD and bidirectional FD. We consider the cases where the traffic is symmetric in DL and UL and when the offered load between both links is asymmetric. Furthermore, the analysis of the traffic constraints is provided with both TCP and UDP traffic. The results are presented in terms of throughput and delay and they show that the increased interference that simultaneous transmission and reception causes is one of the main limiting factors in achieving the promised full-duplex throughput gain. Large traffic asymmetries between DL and UL further compromise such gain. Nevertheless, FD shows potential in asymmetric traffic applications where the lightly loaded needs to be improved, both in terms of throughput and delay.
The structure of the paper is as follows: Section 2 presents our own developed test bed and the most recent results; Section 3 describes the envisioned 5G system featuring FD communication; Section 4 introduces the simulation environment, including the simulation tool and the simulation setup; Section 5 discusses the results; Section 6 describes the future work; finally, Section 7 concludes the paper.
The used hardware has the capability of canceling maximum ∼70 dB for a 20-MHz LTE signal (LTE20) with respect to phase noise. The achievable active cancellation is limited by the power amplifier (PA) non-linearity and the auxiliary transmitter resolution. Under these two limitations, a total active cancellation gain of 63 dB for a LTE20 signal could be demonstrated, with a joint usage of the analogue cancellation and the time domain digital cancellation stages. There are two approaches to achieve such gain. The first one is the option A depicted in Fig. 1 that uses a nonlinear intermodulation approach via Hammerstein PA model  within the digital SIC stage. This option employs the digital transmit signal as input . The second approach, plotted as the option B in Fig. 1, uses the PA signal as direct input to the digital SIC stage with the need of an additional receiver, named the permanent measurement receiver, which contains the transmitter RF impairments and is common in a typical commercial RF design for PA linearization purposes.
The design shown in Fig. 1 also requires the usage of an additional transmit chain. Such additional transmit block has the purpose to protect the receiver against saturation, and it has the advantage that scales only with the number of transmit antennas, which is highly appropriate in MIMO systems. Furthermore, to avoid extra complexity and provide simpler hardware integration, all transmitted antenna streams are input to the same analogue and digital SIC modeling block.
3.1 Featured 5G system design
Since the goal of this work is to study FD in dense small cell networks considering system level aspects, in this section, we are going to describe the small cell concept which will be the reference for our evaluation.
Using the same frame structure for both UL and DL allows for a straightforward extension of the envisioned 5G concept to FD transmission. Note that the control part remains as HD, in order to support different types of FD communication. The cell operations are as follows: firstly, the BS sends the scheduling grant (SG) in the DL control symbol of TTI n . The SG includes the scheduled UE and the transmission parameters, i.e., the direction (UL or DL), the modulation and coding scheme (MCS) and the number of spatial streams used for transmission, often referred as transmission rank. The configuration specified in the SG is applied in TTI n+1 assuming a certain processing time. Consequently, there is one TTI delay between the scheduling and the corresponding data transmission. The UEs send the scheduling request (SR) in the UL symbol, including buffer information, HARQ feedback and the MCS and rank derived from their channel measurements. Notice that there is a delay between the instant when the channel is measured and the TTI when the transmission occurs, which may affect the link adaptation procedure. In addition, since the transmission direction may change at each TTI, creating sudden changes in the interference pattern, it further compromises the link adaptation procedure.
Residual self-interference. For a FD node to be operational, a high level of isolation between the transmitting antenna and the receiving antenna located in the same device is required. Current levels of achievable SIC may not sufficient to bring the SI power below the receiver noise power level, thus leaving a residual interference that affects the SINR.
Increased interference. The number of interfering streams with FD are doubled compared to HD, thus leading to an increased network interference (inter-cell and intra-cell interferences). Then, when the interference is stronger, the data rates are lower and consequently a larger number of TTIs is needed to transmit the same amount of data.
Simultaneous UL and DL data. The availability of simultaneous UL and DL traffic dictates the probability of exploiting FD. Hence, large asymmetries between UL and DL may jeopardize the FD gain.
3.2 Radio resource management architecture
HD and BS FD: for these two cases, the procedure to extract the optimal link direction is the same. In BS FD, a UE cannot be scheduled in both links because it operates in HD transmission mode. The transmission direction is decided based on the offered load of each link, and thus the amount of dedicated resources is proportional to the offered load. For example, let us assume asymmetric traffic, where the highly loaded link (DL) offers k times more load than the lightly loaded link (UL). In this case, the DL would get, in average, k times more resources than the UL, and it would have higher priority. Consequently, the UL would have to wait longer to be scheduled. Furthermore, the algorithm also takes into account fairness, by granting a minimum amount of resources to a link, in order to avoid its starvation. For more details about the used scheme, the reader should refer to . The possible output directions in this case are DL, UL or MUTE. The latter corresponds to the case where both UL and DL buffers are empty.
Bidirectional FD: the transmission direction is based only on the buffer state. For each user, the direction decision block checks if there is data in both the DL and UL buffers. In case of bidirectional FD, simultaneous transmission and reception will only be exploited in case a UE can be scheduled in both links, which will happen only when both UL and DL buffers are filled with data. Then, if this is the case, the transmission direction for that user is DL+UL. Otherwise, it is DL(UL) if the UL(DL) buffer is empty and the DL(UL) is not, or MUTE if the UL and DL buffers are both empty.
In case of BS FD, a FD transmission is performed if two different UEs with opposite link directions can be scheduled; otherwise, the TTI is going to be HD. In case of bidirectional FD, it will be possible to exploit FD if at least one user has associated the DL+UL state. Note that in both cases, scheduling a FD transmission is always given priority over scheduling a HD one.
3.3 Interaction between full duplex and TCP
BW = 200 MHz; f c = 3.5 GHz
1 (whole band)
WINNER II A1 w/fast fading 
10 dBm (BS and UE)
Link adaptation filter
Log average of five samples
Transmission rank scheme
Fixed or taxation-based
Metric (HD and BS FD) and traffic based (bidirectional FD)
HARQ max retransmissions
HARQ combining efficiency η
∼ 25, 50, and 75% if symmetric or asymmetric traffic
100% if full buffer traffic
UDP and TCP
Simulation time per drop
Up to 20 s
Number of simulation drops
4.1 Simulation tool
where P T refers to the transmit power, α d is the pathloss between the transmitter and the intended receiver, N is the receiver noise power, and α i is the pathloss between the interfering nodes and the intended receiver.
where n refers to the transmission number, SINR i is the SINR for the ith transmission/retransmission of the same packet, and η is the combining efficiency, used to model the non-ideality of the combining process. In this study, it is set to 1.0 for simplicity.
where TTI t=TX refers to a DL HD, UL HD, or FD transmission and TTI t=MUTE refers to the case where there is no data to be transmitted in any of the two link directions. The upper limit in the summation T represents the total number of simulated TTIs. The RU is an indication of how saturated is the system. If the system is saturated, it would be translated into high level of interference and vice versa. For example, a RU of 50% means that half of the time the channel is free and a RU of 100% indicates that the channel is always busy.
where TTI t=x refers to the type of communication performed on a TTI. Then, t can be FD or HD.
4.2 Simulation setup
Such gain represents an increase in terms of throughput and a reduction in terms of delay; therefore for the first case, a gain will be indicated by the symbol “ + ” and in the second case it will be indicated by “ −”.
The results provided in this section are presented in an order that aims at analyzing the impact of the increased interference caused by FD and the traffic constraints. In the first subsection, we focus on the analysis of the single cell network to avoid the impact of the inter-cell and intra-cell interference.
The multi-cell scenario will be analyzed in the second and third subsections. In first place, only the impact of ICI is quantified. For this reason, the bidirectional FD performance is analyzed by varying the penetration wall loss. Then, in the last subsection, the jointly effect of the ICI, the intra-cell interference (only for BS FD) and traffic constraints are evaluated.
5.1 Analysis of the traffic constraint limitation
5.2 Analysis of the inter-cell interference limitation
5.3 FD performance under the impact of increased interference and traffic constraints
In this last analysis, the joint impact of the increased interference caused by FD communication and the traffic constraints is analyzed. To that purpose, the multi-cell scenario with symmetric (1DL:1UL) and asymmetric (6DL:1UL) traffic and the rank adaptation algorithm described in Section 4 are used. The performance of HD and both types of FD communication with UDP and TCP for the medium load case (HD RU ≈ 50%) is presented.
TP gain and delay reduction of bidirectional FD and BS FD over HD with asymmetric TCP and UDP traffic in the multi-cell scenario
DL TP (%)
UL TP (%)
DL delay (%)
UL delay (%)
From this intensive analysis of the FD performance in 5G ultra-dense small cell networks, we can conclude that in interference-limited scenarios, the use of FD is not always beneficial. The fact that simultaneous transmission and reception doubles the amount of interfering streams has a negative impact on the system performance. However, a combination of FD and HD transmission modes may provide the optimal system performance. Finally, results indicate that FD shows potential in asymmetric traffic applications where the lightly loaded link needs to be enhanced.
Future research could analyze how non-ideal self-interference cancellation and larger traffic asymmetries between the UL and DL directions impact the results presented in this work, since they provide an upper bound of the achievable FD gain. Furthermore, the use of full duplex could be studied in the context of macro-cell scenarios, where on the other side, the self-interference is much higher in macro BS and can jeopardize the performance. In this case, MAC schemes that take into account the distance among the nodes and power control can be designed to get the most benefit from the usage of full-duplex communication. Another interesting scenario could be the one where not all the user equipments are full duplex capable, i.e., a combination of bidirectional full duplex and base station only full duplex. Finally, the potential of simultaneous transmission and reception to provide fast discovery on the context of device-to-device (D2D) communication can be studied.
The findings presented in this paper could be applied to design a hybrid HD/FD scheduling mechanism that obtains the maximum benefit from both types of communication.
This work analyzes the potential of full-duplex technology in enhancing the throughput and delay of 5G ultra-dense small cell networks. The self-interference cancellation capabilities are investigated using our own developed test bed. The carried experiment proves that up to ∼100 dB of isolation between the transmitting and the receiving antennas placed in the same device are currently achievable, according to the used setup. Then, the potential of full-duplex communication is studied via detailed system level simulations. Results show that achieving the theoretical double throughput gain that FD promises can only be achieved under specific assumptions, namely ideal self-interference cancellation, isolated cells, and full buffer traffic model. However, the promised gain is reduced when realistic assumptions, such as traffic constraints and the inter-cell interference, are considered. Simulations prove that when the traffic profile allows the system to use full-duplex communication, the increased interference caused by simultaneous transmission and reception becomes the main limiting factor in achieving the theoretical FD throughput gain. In case where only the base station is full duplex capable, the intra-cell interference has a significant impact on the system performance.
This work proves that full-duplex communication is able to accelerate the dynamics of TCP and mitigate the drawbacks introduced by such protocol. Furthermore, results of such technology has a compelling potential for applications with asymmetric traffic where the lightly loaded link can benefit in terms of throughput and delay.
The authors declare that they have no competing interests.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
- Cisco, Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, 2015-2020 (2016).Google Scholar
- P Mogensen, et al, in 2014 IEEE 79th Vehicular Technology Conference (VTC Spring). Centimeter-wave concept for 5g ultra-dense small cells (Seoul, 2014), pp. 1–6, doi:10.1109/VTCSpring.2014.7023157.
- JI Choi, et al, in Proceedings of the 16th Annual International Conference on Mobile Computing and Networking (Mobicom). Achieving single channel, full duplex wireless communication (ACMNew York, 2010), pp. 1–12, doi:10.1145/1859995.1859997.Google Scholar
- E Aryafar, et al, in Proceedings of the 18th Annual International Conference on Mobile Computing and Networking (Mobicom). MIDU: enabling MIMO full duplex (ACMNew York, 2012), pp. 257–268, doi:10.1145/2348543.2348576.View ArticleGoogle Scholar
- S Hong, et al, Applications of self-interference cancellation in 5G and beyond. IEEE Commun. Mag.52(2), 114–121 (2014). doi:10.1109/MCOM.2014.6736751.View ArticleGoogle Scholar
- M Heino, et al, Recent advances in antenna design and interference cancellation algorithms for in-band full duplex relays. IEEE Commun. Mag.53(5), 91–101 (2015). doi:10.1109/MCOM.2015.7105647.View ArticleGoogle Scholar
- E Everett, A Sahai, A Sabharwal, Passive self-interference suppression for full-duplex infrastructure nodes. IEEE Trans. Wireless Commun.13(2), 680–694 (2014). doi:10.1109/TWC.2013.010214.130226.View ArticleGoogle Scholar
- KM Thilina, et al, Medium access control design for full duplex wireless systems: challenges and approaches. IEEE Commun. Mag.53(5), 112–120 (2015). doi:10.1109/MCOM.2015.7105649.View ArticleGoogle Scholar
- G Liu, FR Yu, H Ji, VCM Leung, X Li, In-band full-duplex relaying: a survey, research issues and challenges. IEEE Commun. Surv. Tutorials. 17(2), 500–524 (2015). doi:10.1109/COMST.2015.2394324.View ArticleGoogle Scholar
- T Riihonen, S Werner, R Wichman, EZ B., in IEEE 10th Workshop on Signal Processing Advances in Wireless Communications. On the feasibility of full-duplex relaying in the presence of loop interference (Perugia, 2009), pp. 275–279, doi:10.1109/SPAWC.2009.5161790.
- D Bharadia, S Katti, in Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation. Full duplex MIMO radios. NSDI’14 (USENIX AssociationBerkeley, 2014), pp. 359–372. http://dl.acm.org/citation.cfm?id=2616448.2616482.Google Scholar
- X Xie, X Zhang, in Proceedings of IEEE INFOCOM. Does full-duplex double the capacity of wireless networks? (Toronto, 2014), pp. 253–261, doi:10.1109/INFOCOM.2014.6847946.
- BP Day, et al, in Conference on Signals, Systems and Computers (ASILOMAR), 60. Full-duplex bidirectional MIMO: achievable rates under limited dynamic range, (2012), pp. 3702–3713. IEEE Transactions on Signal Processing. doi:10.1109/ACSSC.2011.6190243.
- AC Cirik, R Wang, Y Hua, in Conference on Signals, Systems and Computers (ASILOMAR), 63. Weighted-sum-rate maximization for bi-directional full-duplex MIMO systems, (2015), pp. 801–815. IEEE Transactions on Communications. doi:10.1109/ACSSC.2013.6810575.
- NH Mahmood, et al, in 2015 IEEE 81st Vehicular Technology Conference (VTC Spring). On the potential of full duplex communication in 5G small cell networks (Nanjing, 2015), pp. 1–5, doi:10.1109/VTCSpring.2015.7145975.
- W Zhou, K Srinivasan, in 2014 International Conference on Signal Processing and Communications (SPCOM). Sim+: a simulator for full duplex communications (Bangalore, 2014), pp. 1–6, doi:10.1109/SPCOM.2014.6983995.
- Z Tong, M Haenggi, Throughput analysis for full-duplex wireless networks with imperfect self-interference cancellation. IEEE Trans. Commun.63(11), 4490–4500 (2015). doi:10.1109/TCOMM.2015.2465903.View ArticleGoogle Scholar
- M Mohammadi, HA Suraweera, I Krikidis, C Tellambura, in IEEE International Conference on Communications (ICC). Full-duplex radio for uplink/downlink transmission with spatial randomness (London, 2015), pp. 1908–1913, doi:10.1109/ICC.2015.7248604.
- R Zhang, et al, in 2015 IEEE International Conference on Communications (ICC). Investigation on DL and UL power control in full-duplex systems (London, 2015), pp. 1903–1907, doi:10.1109/ICC.2015.7248603.
- S Goyal, et al, Full duplex cellular systems: will doubling interference prevent doubling capacity?. IEEE Commun. Mag.53(5), 121–127 (2015). doi:10.1109/MCOM.2015.7105650.View ArticleGoogle Scholar
- H Malik, M Ghoraishi, R Tafazolli, in Networks and Communications (EuCNC), 2015 European Conference On. Cross-layer approach for asymmetric traffic accommodation in full-duplex wireless network (Paris, 2015), pp. 265–269, doi:10.1109/EuCNC.2015.7194081.
- NH Mahmood, et al, in 11th International Conference on Wireless and Mobile Communications (ICWMC). Throughput analysis of full duplex communication with asymmetric traffic in small cell systems (St. Julians, 2015), pp. 57–60.Google Scholar
- L Wang, et al, Exploiting full duplex for device-to-device communications in heterogeneous networks. IEEE Commun. Mag.53(5), 146–152 (2015). doi:10.1109/MCOM.2015.7105653.View ArticleGoogle Scholar
- W John, S Tafvelin, in 2008 International Conference on Information Networking. Heuristics to classify internet backbone traffic based on connection patterns (GinoWan, 2008), pp. 1–5, doi:10.1109/ICOIN.2008.4472818.
- J Postel, Transmission Control Protocol. [Online]. Available: http://www.ietf.org/rfc/rfc793.txt (1981, updated by RFCs 1122, 3168, 6093, 6528).
- M Allman, V Paxson, W Stevens, Congestion Control to TCP’s Fast Recovery Algorithm. (1999, TCP, [Online]. Available: http://www.ietf.org/rfc/rfc2581.txt (obsoleted by RFC 5681, updated by RFC 3390).
- m. Duarte, C Dick, A Sabharwal, Experiment-driven characterization of full-duplex wireless systems. IEEE Trans Wireless Commun. 11(12), 4296–4307 (2012). doi:10.1109/TWC.2012.102612.111278.View ArticleGoogle Scholar
- A Sahai, et al, On the impact of phase noise on active cancelation in wireless full-duplex. IEEE Trans. Veh. Technol.62(9), 4494–4510 (2013). doi:10.1109/TVT.2013.2266359.MathSciNetView ArticleGoogle Scholar
- D Korpi, et al, in IEEE Global Communications Conference (GLOBECOM). Adaptive nonlinear digital self-interference cancellation for mobile inband full-duplex radio: algorithms and RF measurements (San Diego, 2015), pp. 1–7, doi:10.1109/GLOCOM.2015.7417188.
- L Anttila, et al, in 2014 IEEE Globecom Workshops (GC Wkshps). Modeling and efficient cancellation of nonlinear self-interference in MIMO full-duplex transceivers (Austin, 2014), pp. 777–783, doi:10.1109/GLOCOMW.2014.7063527.
- 3rd Generation Partnership Project, Technical Specification Group Radio Access Network; Enhanced performance requirement for LTE User Equipment (UE) (2015). 3GPP TR 36.829, Enhanced performance requirement for LTE User Equipment (UE), Release 11.Google Scholar
- MG Sarret, et al, in 2014 11th International Symposium on Wireless Communications Systems (ISWCS). Improving link robustness in 5G ultra-dense small cells by hybrid arq (Barcelona, 2014), pp. 491–495, doi:10.1109/ISWCS.2014.6933403.
- N Mahmood, D Catania, M Lauridsen, G Berardinelli, P Mogensen, F Tavares, K Pajukoski, A Novel Centimeter-Wave Concept for 5G Small Cells. Opportunities in 5G Networks: A Research and Development Perspective. CRC Press LLC, 5th April 2016. (F Hu, ed.) (CRC Press LLC, 2016).Google Scholar
- S Floyd, T Henderson, A Gurtov, The New Reno Modification to TCP’s Fast Recovery Algorithm. (2004 [Online]. Available: http://www.ietf.org/rfc/rfc3782.txt (obsoleted by RFC 6582).
- D Catania, et al, in 2015 IEEE 81st Vehicular Technology Conference (VTC Spring). A distributed taxation based rank adaptation scheme for 5G small cells (Glasgow, 2015), pp. 1–5, doi:10.1109/VTCSpring.2015.7145600.
- M Abramowitz, IA Stegun, LTE for UMTS - OFDMA and SC-FDMA Based Radio Access. (H Holma, A Toskala, eds.) (Wiley, 2009).Google Scholar
- 3rd Generation Partnership Project, Further advancements for E-UTRA physical layer aspects (Release 9) (2010). 3GPP TR 36.814, Evolved Universal Terrestrial Radio Access (E-UTRA); Further advancements for E-UTRA physical layer aspects, Release 9.Google Scholar
- 3rd Generation Partnership Project, Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA) Radio Link Control (RLC) protocol specification (20016). 3GPP TS 36.322, Evolved Universal Terrestrial Radio Access (E-UTRA); Radio Link Control (RLC) protocol specification, Release 8.Google Scholar
- J Postel, Internet Standard, User Datagram Protocol. 28th August 1980, RFC 768 (1980). https://tools.ietf.org/html/rfc768.
- Radio WWIN, WINNER II channel models (2008). Internet Standard, User Datagram Protocol, J. Postel, 28th August 1980, RFC 768. www.cept.org/files/1050/documents/winner2\%20-\%20final\%20report.pdf.