 Research
 Open Access
Downlink performance of cell edge using cooperative BS for multicell cellular network
 Md Hashem Ali Khan^{1},
 JinGyun Chung^{1} and
 Moon Ho Lee^{1}Email author
https://doi.org/10.1186/s1363801605370
© Khan et al. 2016
Received: 8 October 2014
Accepted: 26 January 2016
Published: 20 February 2016
Abstract
We consider the downlink of a multicell system comprised of base stations (BSs) and user terminals equipped with multiple antennas respectively on the condition that arbitrary BS cooperation and distance dependent propagation path loss are assumed. In this paper, we consider homogeneous networks for the rectangular coordinates and show the cell edge performance of cellular networks based on distance from their cell center, i.e., BS. We focus on the downlink capacity of edge users in the cellular networks and show that BS cooperation can improve the spectral efficiency. The BSs cooperate for their transmission to the cell edge users in order to improve their signaltointerferenceplusnoise ratio (SINR) for intercell interference (ICI) cancelation in downlink multicell systems. When fractional frequency reuse (FFR) is applied to the cell edge, it is conjectured that BS cooperation, or a coordinated multipoint (CoMP), will further improve the system performance. Simulation results show that the proposed scheme outperforms the reference schemes in terms of the cell edge SINR with a minimal impact on the path loss exponent in the networks.
Keywords
1 Introduction
In conventional cellular networks, a major degrading factor affecting the system performance is intercell interference (ICI). This is caused by neighboring cells using the same frequency band. The ICI can cause significant performance loss at user (mobile station (MS)) terminals, especially, at cell edge users located in the vicinity of cell boundaries. Various techniques have been recommended to mitigate ICI [1, 2]. Users close to the base station (BS) typically have a high mean signaltointerferenceplusnoise ratio (SINR), whereas, the users at cell intersections suffer from low SINR levels. Multiinput multioutput (MIMO) has emerged as a key method to achieve high spectrum and power efficiency in mobile communication [3, 4]. Though the capacity region of MIMO broadcast channel (BC) is an unsolved problem for lack of a general theory on nondegraded broadcast channels, an achievable region for MIMO broadcast channel was obtained by applying the dirty paper coding (DPC) [5] at the transmitter [6–8] which established the duality of achievable region and the capacity region of the MIMO. This makes the solution of sum capacity of MIMO BC possible, since the solution of sum capacity of MIMO BC is in general a nonconvex optimization, while MIMO multiple access channel can be solved by convex optimization. In this paper, we consider a multicell network, where primary cell edge users suffer severe ICI due to their location on the cell boundary. As a solution, we explore the problem of ICI mitigation on the primary cell edge users by deploying cells at the borders of adjacent primary cells to serve primary cell edge users. The cell edge problem of this system is addressed. In [9–11], it is shown that with the optimal power control, such BS cooperation eliminates the intercell interference penalty. In other words, a network of interfering cells has the same percell capacity as a single, isolated cell.
In order to further reduce the complexity of the joint cooperation and coordination strategies, the emerging distributed solutions to the intriguing multicell capacity maximization problem have drawn more and more attention, with only local information achievable [12–14]. Typically, the frequency reuse factor is much less than unity, so that the level of cochannel interference is low. Thus, interference is controlled by fixing the frequency reuse pattern and the maximum power spectral density levels of each base station. We analyze the cooperation scenario in a multicell environment where the other cell interference is significant. The capacity achieved through cooperation is shared equally among the cell edge users, i.e., resources are shared fairly among the cooperating users. The transmission rate to each user is determined based on the SINR. Cooperative transmission by three BSs can improve this SINR by transmitting jointly to one user at a time.

➢ We consider a new multicell structure for the downlink system. Multicell downlink is a cooperative technology which coordinates multiple separated cells. It improves the performance of cell edge for ICI cancelation in BS cooperative downlink systems.

➢ It is well known that a major drawback of this system is having strong interference since users located at cell edges may experience much interference from signal transmitted in adjacent cells.

➢ We try to quantify the cell edge performance of cellular systems with and without ICI according to the distance from their cell center.

➢ We consider 19 cells composed of two tiers. MSs in the cell edge determined by the polar and rectangular coordinates experience the interference.

➢ We note that at a path loss exponent of 3.6, we observe an approximately 13dB improvement in cell edge SINR by using reuse of three relative to reuse of one based on FFR. A reuse of seven increases cell edge SINR by 8 dB.
The rest of this paper is organized as follows. The system model is described in Section 2. In Section 3, we discuss multicell cooperation scheme. In Section 4, we address intercell interference technique control. In Section 5, we are amenable to analysis for multicell cellular systems with ICI. In Section 6, we introduce power constraint for per base station and simulation results in Section 7. Finally, we conclude the paper in Section 8.
2 System model
3 Multicell cooperation scheme
BS cooperation entails sharing control signals, transmit data, user propagation channel state information (CSI), and precoders via highcapacity wired backhaul links to coordinate transmissions. BS cooperation approach is feasible; the BSs are connected by a highspeed wired backbone that allows information to be reliably exchanged among them. Full cooperation leads to the highest sum rates at the cost of increased overhead due to global CSI requirements and the exchange of a greater amount of information among BSs, including CSI, transmit data, and precoding data. In the BS cooperation schemes, the CSI at the BSs plays an important role in maximizing the system performance. The BSs use this information to adapt their transmission strategies to the channel conditions. We analyze the cooperation scenario in a multicell environment where the other cell interference is significant. The capacity achieved through cooperation is shared equally among the cell edge users, i.e., resources are shared fairly among the cooperating users. The transmission rate to each user is determined based on the signaltointerferenceplusnoise ratio (SINR). Cooperative transmission by two base stations can improve this SINR by transmitting jointly to one user at a time. However, this improvement in terms of throughput may not always be enough to increase the throughput of each user. The signals from the serving BS and from the neighbor BS arrive at the terminal at the same time, i.e., received signals by the terminal from the two BSs are frame synchronized.
Moreover, the maximizing system performance is also accompanied by the overhead cost for the CSI acquisition via channel training and feedback in frequency division duplex (FDD) systems. It needs to scale proportionally to the number of transmit and receive antennas as well as the number of users in the system in order to maintain a constant gap of the sum rate with respect to the full CSI case. The cooperative BSs via a wired backbone network brings about huge data traffic and information.
3.1 No cooperation
3.2 Cooperation
The factor δ in Eqs. (8)–(9) defines the proportion of resource sharing among the terminals under cooperation. In our system, considering resource fairness, the value for δ is 1/2.
Hence, it is worthwhile for the user to decide whether to perform cooperation in the downlink channel.
4 Intercell interference technique control
In this section, we provide the cell edge performance for rectangular coordinate. The performance of cell edge is usually either noise limited or interference limited [21]. In noiselimited situation which typically occurs in large cells in the rural areas, the performance can be usually be improved by providing a power gain.
4.1 Intercell interference: an example 2cell case
We note that SINR degrades with increasing d. Also, for a given d < R, the SINR is higher for a larger path loss exponent α. This is because the interference travels a longer distance for d < R and is attenuated more for larger α. We also note that the maximum SINR at the cell edge with d = R is limited to 0 dB.
However, in case of downlink using multiuser MIMO, it is possible that many users located at the cell edge are receiving to their corresponding cell (BS2) in the downlink as shown in Fig. 3. A user receiving in BS2 from the cell edge will see these multiple interferers transmitted at BS2 with approximately the same power as its own transmitted power at BS2. When the number of these interfering BS1 users is greater than 2, the SINR seen on the downlink can be lower than the uplink SINR in interference limited scenarios.
4.2 Multicell for frequency reuse case: cell edge performance
We apply frequency reuse, so the users at the cell edge may suffer a high degree of interference from neighboring cells. Multiple neighboring cells have channel information of edge users, and they coordinate for the data transmission: one of these cells is selected to act as the home cell to transmit data to such a user, and other neighboring cells will take this user into consideration when designing precoding matrices. With precancelation of intracell interference provided by the home cell and precancelation of ICI at other neighboring cells, there will be no interference for this edge user from those cells.
With such a coordination strategy, the interference for both cell interior and cell edge users is efficiently mitigated. FFR is another technique for interference management where BSs cooperatively schedule users in different downlink bandwidths. However, FFR is a frequency domain interference management technique. This technique coordination strategy is a spatial domain technology that can be implemented with a universal frequency reuse.
The main idea of intercell coordination is to do interference precancelation at all the neighboring cells for the active edge user and select one cell to transmit information data to this user. The precoding technique used for intercell coordination is multicell MIMO, the same as for intracell coordination. Each edge user selects a cell based on the channel state, denoted as the home cell, while the other neighboring cells act as helpers for the data transmission. The remaining cells are interferer cells.
4.2.1 Case I: reuse1
4.2.2 Case II: reuse3
4.2.3 Case III: reuse7
Comparison of frequency reuse
Frequency reuse  SINR  Cell edge channel capacity 

Reuse1  \( {\mathrm{SINR}}_{\mathrm{reuse}\hbox{} 1}=\frac{1}{2+3\times {(2)}^{\alpha }} \)  \( {C}_{\mathrm{reuse}\hbox{} 1}=1.{ \log}_2\left(1+{\mathrm{SINR}}_{{}_{\mathrm{reuse}\hbox{} 1}}\right) \) 
Reuse3 Reuse7  \( {\mathrm{SINR}}_{\mathrm{reuse}\hbox{} 3}=\frac{3}{3\times {(2)}^{\alpha }+6\times {(2.7)}^{\alpha }} \) \( {\mathrm{SINR}}_{\mathrm{reuse}\hbox{} 7}=\frac{7}{(2)^{\alpha }+4\times {(2.7)}^{\alpha }} \)  \( {C}_{\mathrm{reuse}\hbox{} 3}=\left(\frac{1}{3}\right){ \log}_2\left(1+{\mathrm{SINR}}_{{}_{\mathrm{reuse}\hbox{} 3}}\right) \) \( {C}_{\mathrm{reuse}\hbox{} 7}=\left(\frac{1}{7}\right){ \log}_2\left(1+{\mathrm{SINR}}_{{}_{\mathrm{reuse}\hbox{} 7}}\right) \) 
5 Performance analysis for multicell cellular network with ICI
6 Power constraints for per base stations
The solution of (35) subject to the sum power constraint is given by the water filling. It follows that the dual problem can be solved by the vector of dual variables λ.
7 Simulation results
Simulation parameters
Parameters  Value 

Number of cells  19 
Number of cooperation BSs  7 
Cell shape  Hexagon diagram 
BS position  On circle with radius 
User position  Cell edge 
(BS, user) antenna number  (7, 3) 
Carrier frequency  2 GHz 
Bandwidth  10 MHz 
Lognormal shadowing  Gaussian distribution with zero mean, 10dB standard deviation 
Transmission power (BS)  46 dBm 
SNR  −15 to 20 dB 
Path loss exponent  α = 3.5 
Path loss  128.1 + 37.6log_{10} (d) 
Fading  i.i.d. Rayleigh 
8 Conclusions
In this paper, we focus on increasing the cell edge capacity in the multicell networks. We also propose the deployment scheme consisting of 19 cells with two tiers for the rectangular coordinate and show the cell edge performance of cellular systems with and without ICI according to the distance from their BSs. We show that 13dB improvement in the cell edge SINR with frequency reuse factor of three can be achieved compared to frequency reuse factor of one. BS cooperation has been proposed to mitigate the cell edge effect. The multicell coordinated MUMIMO scheme is proposed to improve the cell edge user throughput, which can satisfy higher spectral efficiency requirements of the LTE Advanced systems as well as the capacity by maximizing the number of cooperative cells/BSs.
Declarations
Acknowledgements
This work was supported by the MEST 2015R1A2A1A 05000977, NRF, Korea.
Open AccessThis 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.
Authors’ Affiliations
References
 A Yousafzai, MR Nakhai, Block QR decomposition and nearoptimal ordering in intercell cooperative multipleinput multipleoutputorthogonal frequency division multiplexing. IET Commun. 4(12), 1452–1462 (2010)View ArticleMathSciNetMATHGoogle Scholar
 TA Le, MR Nakhai, Downlink optimization with interference pricing and statistical CSI. IEEE Trans. Commun. 61(6), 2339–2349 (2013)View ArticleGoogle Scholar
 E Telatar, Capacity of multiantenna Gaussian channels. European Trans. Telecom 10(6), 585–595 (1999)View ArticleGoogle Scholar
 Q. H. Spencer, C. B. Peel, A. L. Swindlehurst, M. Haardt, An introduction to the multiuser MIMO downlink, IEEE Commun. Mag. 42(10), 60–67 (2004) [Publisher: IEEE].Google Scholar
 M Costa, Writing on dirty paper. IEEE Trans. Inf. Theory 29, 439–441 (1983)View ArticleMATHGoogle Scholar
 P Viswanath, D Tse, Sum capacity of the vector Gaussian broadcast channel and uplinkdownlink duality. IEEE Trans. on Inf. Theory 49, 1912–1921 (2003)View ArticleMathSciNetMATHGoogle Scholar
 W Yu, JM Cioffi, Sum capacity of Gaussian vector broadcast channels. IEEE Trans. on Inf. Theory 50(1), 1875–1892 (2004)View ArticleMATHGoogle Scholar
 H. Weingarten, Y. Steinberg, and S. Shamai, The capacity region of the Gaussian MIMO broadcast channel, IEEE Trans. on Int. Theory. 52(9), 3936–3964 (2004) [Publisher: IEEE]Google Scholar
 Physical layer aspects for evolved Universal Terrestrial Radio Access (UTRA), 3GPP Technical Report (TR) 25.814 V7.1.0, (Release 7) 200609.Google Scholar
 D Gesbert, S Hanly, H Hung, SS Shitz, O Simeone, W Yu, Multicell MIMO cooperative networks: a new look at interference. IEEE Journal of Selected Areas in Communications 28, 9 (2010)Google Scholar
 R Zhang, Cooperative multicell block diagonalization with perbasestation power constraints. IEEE J. Sel. Areas Commun. 28(9), 1435–1445 (2010)View ArticleGoogle Scholar
 S. Boyer, L. Vandenberghe, Convex optimization (Cambridge University Press, Cambridge, CB2 8RU, UK , Chapter 4, 2004)Google Scholar
 M Fallgren, An optimization approach to joint cell, channel and power allocation in multicell relay networks. IEEE Trans. Wirel. Commun. 11(8), 2868–2875 (2012)Google Scholar
 S Kiani, D Gesbert, Optimal and distributed scheduling for multicell capacity maximization. IEEE Trans. Wirel. Commun. 7(1), 288–297 (2008)View ArticleGoogle Scholar
 LC Wang, CJ Yeh, 3cell network MIMO architectures with sectorization and fractional frequency reuse. IEEE J. on Sel. Areas in Commun. 29, 1185–1199 (2011)View ArticleGoogle Scholar
 L. Xu, K. Yamamoto, H. Murata, S. Yoshida, Cell edge capacity improvement by using adaptive base station cooperation in cellular networks with fractional frequency reuse, IEICE Transactions on Communications. E93B(7) 1912–1918 (2010)Google Scholar
 SH Ali, VCM Leung, Dynamic frequency allocation in fractional frequency reused OFDMA networks. IEEE Trans. on Commun. 8, 8 (2009)Google Scholar
 A Mahmud, KA Hamdi, N Ramli, Performance of fractional frequency reuse with comp at the celledge. 2014 IEEE Region 10 Symposium, 2014. MalaysiaView ArticleGoogle Scholar
 OFDMA, Downlink intercell interference mitigation, 3GPP Project Document R1060 291, 2006. Available: http://www.3gpp.org
 R1050507: Soft frequency reuse scheme for UTRAN LTE, Huawei 3GPP TSG RAN WG1 Meeting no.41 Athens, Greece, 2005.Google Scholar
 F. Khan, LTE for 4G Mobile Broadband air Interface Technologies and Performance, (Cambridge University Press, Chapter 16 (pp. 409425), ISBN: 9780521882217, 2009)Google Scholar
 M Rahman, H Yanikomeroglu, Enhancing cell edge performance: a downlink dynamic interference avoidance scheme with intercell coordination. IEEE Trans. on Wireless Comm. 9, 4 (2010)View ArticleGoogle Scholar
 X You, D Wang, P Zhu, B Sheng, Cell edge performance of cellular mobile systems. IEEE Trans. on Selected Areas in Communications 29, 6 (2011)View ArticleGoogle Scholar
 JVB James, B Ramamurthi, Distributed cooperative precoding with SINR based cochannel user grouping for enhanced cell edge performance. IEEE Trans. on Wireless Comm. 10, 9 (2010)Google Scholar
 H Huh, AM Tulino, G Caire, Network MIMO with linear zeroforcing beamforming: large system analysis, impact of channel estimation, and reducedcomplexity scheduling. IEEE Trans. on Inf. Theory 58, 5 (2012)View ArticleMathSciNetGoogle Scholar
 N Ul Hassan, C Yuen, Z Zhang, Optimal power control and antenna selection for multiuser distributed antenna system with heterogeneous QoS constraints (Globecom’12 Workshop: Multicell Cooperation, California, USA, 2012)View ArticleGoogle Scholar
 N. Ul Hassan, C. Yuen, Z. Zhang, Optimal power control between two opportunistic cooperative base stations, IEEE 13th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Cesme, Turkey, 1720 2012. [Publisher: IEEE]Google Scholar