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LETTER
Spectral Efficiency Improvement of Fractional Frequency Reuse by Inter-Cell Interference Cancellation on Cooperative Base Station Kazuki MARUTA†a) , Atsushi OHTA† , Masataka IIZUKA† , and Takatoshi SUGIYAMA† , Members
SUMMARY This paper proposes applying our inter-cell interference (ICI) cancellation method to fractional frequency reuse (FFR) and evaluates the resulting spectral efficiency improvement. With our ICI cancellation method based on base station cooperation, the control station generates ICI replica signals by simple linear processing. Moreover, FFR effectively utilizes frequency resources by both allowing users in the cell-center region to access all available sub-channels and increasing the transmission power to users in the cell-edge region. FFR provides the conditions under which the ICI cancellation method works effectively. Computer simulations show that the average spectral efficiency of the proposed method is comparable to that of cooperative MU-MIMO, which can completely remove ICI. key words: inter-cell interference cancellation, base station cooperation, fractional frequency reuse
1.
Introduction
Since many kinds of broadband wireless systems using the microwave band such as WiMAX [1] or LTE [2] have been developed and are now in wide use, exhaustion of frequency resources is one of the most serious problems in wireless communication. The in-sufficient number of channels is forcing more extensive frequency reuse and inter-cell interference (ICI) is emerging as the key problem degrading system capacity. Cooperative transmission [3] by multiple base stations (BSs) is one of the most promising solutions to control cochannel ICI and improve the spectral efficiency. BS cooperation is essential to meet the requirements of LTE-Advanced [4] in order to increase the capacity for cell-edge users. Most of all studies, however, assume that the number of cooperating BSs is limited due to the practical computational complexity. If widely separated BSs are connected to the same control station (CS), they can be regarded as a distributed antenna array that exhibits low antenna correlation. This arrangement is suitable for applying a multiuser multiple input multiple output (MU-MIMO) [5] technique. However, it is not practical to apply MU-MIMO to systems with a large number of cooperative BSs because its precoding weight calculation for multiuser beamforming using the large size channel matrix is so heavy. This complexity can be reduced by applying clustering approach, in which the cluster consists of cells and BSs in the clusters work cooperatively. Clustering, however, requires frequency reuse with multiple Manuscript received October 1, 2011. Manuscript revised January 30, 2012. † The authors are with NTT Access Network Service Systems Laboratories, NTT Corporation, Yokosuka-shi, 239-0847 Japan. a) E-mail:
[email protected] DOI: 10.1587/transcom.E95.B.2164
frequency channels in order to avoid inter-cluster interference [6], which causes spectral efficiency degradation due to frequency resource division. Therefore, we have studied new approaches which can nearly achieve the performance of cooperative MU-MIMO with single frequency channel. We previously proposed an ICI cancellation method for BS cooperation on the downlink [6], [7]. When the CS knows the transmission signals and the channel state information (CSI) between neighboring BSs and subscriber stations (SSs), the ICI replica signal can be determined by simple linear processing and only subtracted from the transmission signal so that ICI is cancelled at the SS side. Though this method is similar to MU-MIMO processing for ICI removal, its calculation load is greatly reduced. For example, when the number of the cooperating BSs is larger than 20, the proposed method can reduce computational complexity over 90% [6]. In [7], for the conventional frequency reuse environment, we confirmed that the proposed method improves the spectral efficiency and discussed its optimal conditions. Fractional Frequency Reuse (FFR) [8] has been studied to improve the frequency resource utilization. In FFR, the whole bandwidth is divided into sub-channels. All subchannels are allocated to users in the cell-center region because their ICI level is assumed to be relatively small compared to the desired signal level. On the contrary, users in the cell-edge region can use only one sub-channel and different sub-channels are assigned to users in adjacent cells to avoid ICI. Since the BS utilizes only one sub-channel, the signal strength can be intensified because of the remaining transmission power that is available. As a result, frequency resources can be effectively utilized by flexibly controlling the frequency reuse factor (RF) and the transmission power. This paper proposes incorporating our ICI cancellation method into FFR with the expectation of further improving spectral efficiency. Achievable spectral efficiency of the proposed method is investigated and compared to that of MUMIMO which can ideally remove ICI by full BS cooperation. The rest of this paper is organized as follows. Section 2 describes the system model to be discussed. Section 3 presents the proposed method and its application for FFR. Computer simulation results are presented in Sect. 4. Finally, the paper is concluded in Sect. 5.
c 2012 The Institute of Electronics, Information and Communication Engineers Copyright
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by ti = wi si −
M
wi (hii wi )−1 hi j w j s j .
(2)
ji
The second term of (2) is the interference replica signals needed to cancel the second term of (1) at the receiver side. From (1) and (2), the new reception signal yi is now expressed as follows; yi
=
M
hi j tj
M
+ n = hii wi si −
j
Fig. 1
System model: Cooperative ICI cancellation with FFR.
M M M −1 + hi j w j s j − hi j w j h j j w j h jk wk sk +n ji
2.
System Model
ji
= hii wi si −
Figure 1 shows the FFR structure and BS cooperation. M hexagonal shaped cells are uniformly deployed. In the system model, each cell (radius of rcell ) is divided into two regions by a reuse partition boundary rinner . The total bandwidth available for a system is divided into 3 sub-channels. The frame is also divided into two parts. The first part is assigned to SSs in the cell-center region with RF=1 and the latter part is assigned to SSs in the cell-edge region with RF=3. The duration of the part is assumed to be given in proportion to each region area. Though SSs in the cell-edge region use only 1/3 of all bandwidth, the signal strength can be raised by up to 3 times by concentrating the total transmission power on the sub-channel. All BSs are connected to the control station (CS) with a high-speed backhaul. The BSs are synchronized and share the information about the CSI and the transmission signal from each BS. The CS executes signal processing for cooperative downlink transmission to SSs that are assigned the same sub-channel in the same time slot. 3.
Inter-Cell Interference Cancellation Method
M
M j
hi j t j = hii wi si +
M
hi j w j s j + n,
(1)
M
k j
−1 w j h j j w j h jk wk sk + n. (3)
k j
The proposed method replaces the second ICI term of (1) with that of (3), that is, residual ICI. In order to make ICI cancellation effective, the intensity of the second term of (1) needs to be much smaller than that of the first term as indicated by M (4) |hii wi si | hi j w j s j , ji
where |.| denotes the absolute value. By multiplying (hii wi )−1 , the following equation is derived; M (5) |si | (hii wi )−1 hi j w j s j . ji
Then by multiplying hi j w j and taking summation over j, the following relationship is obtained; M M M −1 hi j w j s j hi j w j h j j w j h jk wk sk . (6) ji
k j
According to (6), the intensity of the second term of (3) is much smaller than that of (1). This indicates that the interference from surrounding cells can be suppressed when relationship (4) is satisfied. Therefore, (4) expresses the requirement that must be satisfied for the proposed method to work effectively. Residual ICI in the second term of (3) can be suppressed by generating interference replica signals in the same manner. The transmission signal with the second ICI cancellation component, ti , is described as,
ji
where hii wi si is the desired reception signal of the SS in the i-th cell and hi j w j s j (i j) is interfering reception signal from the surrounding j-th cell. n is an additive white Gaussian noise (AWGN) term. The proposed method adds an ICI cancellation signal and the transmission signal ti is replaced
hi j
ji
ji
Weighted initial transmission signal ti (i = 1, . . . , M) at the i-th cell is written as ti = wi si where si denotes the transmission signal and wi denotes the transmission weight generated from hii . hi j denotes the CSI from BS in the j-th cell to SS in the i-th cell. Though wi is not always necessary in SISO transmission, it is described as a general expression hereafter. Signal yi received by the SS in the i-th cell is written as, yi =
hi j w j s j
ji
ti = wi si −
M
gi j w j s j +
ji
M
gi j
ji
gi j = wi (hii wi )−1 hi j . The resulting reception signal yi is,
M
g jk wk sk ,
(7)
k j
(8)
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yi = hii wi si +
M
hi j
ji
M
g jk
M
k j
gkl wl sl + n.
(9)
lk
In this letter, ICI cancellation up to the second order is applied. 4.
Performance Evaluation
4.1 Simulation Parameters Simulation parameters are shown in Table 1. We focus on the characteristics of the center cell whose order is defined as i=1. In the evaluation, interfering cells are taken into account in the area where received ICI level is more than −20 dB relative to the noise level. Transmission power of BS is defined by average received SNR of SSs at the celledge. For instance, the average cell-edge SNR is set to 10 dB when RF=1. The total transmission power of all BSs is assumed to be constant when practicing cooperative transmission to compare each method appropriately in terms of received SINR. A boundary for reuse partition rinner is determined by averaged SINR which is measured at SS side. According to the path loss model in [9], averaged SINR and rinner (calculated as r11 ) have following relationship; ⎞ ⎛⎜
⎟⎟⎟ ⎜⎜ M 3.1 4 ⎜ 3.1 4 2 SINRave = 10 r11 ⎜⎜⎝ 10 r1 j + E |n| ⎟⎟⎟⎠, (10) j1
where ri j denotes the distance from BS in the j-th cell to SS in the i-th cell and E[.] denotes the expected value. Averaged reception signal power is expressed as E[|hi j |2 ] = 103.1 ri4j from the path loss model. Spectral efficiencies for some parameters of the threshold SINR are evaluated. The spectral efficiency on the downlink of the center cell, Γ, is expressed as follows, 1 log2 (1 + SINR). (11) RF Instantaneous SINR of SS in the center cell for the proposed method is, 2 ⎛ ⎞ ⎜⎜ M M M ⎟⎟⎟ ⎜ ⎜ ⎟ SINR = |h11 w1 |2 ⎜⎜⎜⎜ h1 j g jk gkl wl +|n|2 ⎟⎟⎟⎟. (12) ⎠ ⎝ Γ=
j1
k j
MU-MIMO based on Gram-Schmidt orthogonalization [10] with single frequency reuse is evaluated as follows, 2 ⎛ ⎞ M M M ⎜⎜ ⎟⎟⎟ ⎜⎜ 2⎟ ⎜ SINR = h1 j v j1 ⎜⎝ h1 j v jk + |n| ⎟⎟⎠, (13) j=1 j=1 k1 where vi j denotes elements of the transmission weight matrix, which is calculated from channel matrix composed of hi j . Actually, (13) indicates SNR because MU-MIMO can M perfectly cancels ICI, i.e. Σ M j=1 Σk1 h1 j v jk = 0. Instantaneous SINR of SS randomly deployed in each cell-center/edge region is first calculated from (12) or (13), and then the spectral efficiency Γ is calculated from (11) using the instantaneous SINR value. SSs are uniformly distributed in each cell. All available sub-channels at each cell are assumed to be assigned in every time slot. The duration of the time slot is assumed to be given in proportion to each region area. It yields fairness for the evaluation with the parameters of reuse partition boundary. 4.2 Simulation Results Evaluated cumulative distribution functions (CDFs) of the spectral efficiency for the following five methods: A) Simple single frequency reuse (w/o Cancellation, w/o FFR, RF=1), B) Conventional frequency reuse with 3 sub-channels (w/o Cancellation, w/o FFR, RF=3), C) Simple FFR without ICI cancellation (w/o Cancellation, w/FFR), D) Proposed method (w/Cancellation, w/FFR), and E) Cooperative MUMIMO are shown in Fig. 2. This figure plots FFR performances where the threshold SINR is set to 6 dB. Figures 3 and 4 show the CDF=5% and average values of spectral efficiency for various values of reuse partition threshold SINR, respectively. In the case of RF=1, large spectral efficiency is achieved in the high CDF region because the coefficient 1/RF in (11) is 1, i.e. the bandwidth is not divided. In the case of RF=3, the coefficient 1/RF is 1/3. This reduces frequency resource utilization since the bandwidth is divided into 3 sub-channels. Nevertheless, it works well in the low
lk
As the comparison method, SINR of SS for cooperative Table 1
Simulation parameters.
Fig. 2
CDFs of spectral efficiency.
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Fig. 3
CDF5% spectral efficiency with reuse partition threshold SINR.
works especially well in the high and low CDF region. According to Fig. 3, the spectral efficiency at CDF= 5% of both methods rapidly increases with threshold SINR up to 6 dB where rinner /rcell is 0.64. Varying the spectral efficiency with threshold SINR indicates that many of SSs whose performance is CDF=5% are located around the boundary. When rinner /rcell is 0.64 (i.e. the area of the cellcenter region is around 40% of the cell), SSs in the boundary can sufficiently avoid ICI and good performance is kept in the low CDF region. The average spectral efficiency of both the proposed method and simple FFR method decreases as threshold SINR increases over 6 dB as shown in Fig. 4. This is because the impact of the frequency resource division of 1/3 becomes large when enlarging the cell-edge region with RF=3. When the threshold SINR is set to the optimum value of 6 dB, the average spectral efficiency of the proposed method can closely approach that of cooperative MU-MIMO. As a result of this optimization, the proposed method can better the spectral efficiency of cooperative MU-MIMO in the high and low CDF regions and achieve almost the same average spectral efficiency while solving the problem of heavy computational complexity. 5.
Fig. 4
Average spectral efficiency with reuse partition threshold SINR.
CDF region because ICI is avoided, especially around the cell-edge, compared to the case of RF=1. Performance with FFR almost matches that with RF=1 in the high CDF region and RF=3 in the low CDF region. Since cooperative MUMIMO can completely remove ICI, it is superior to FFR in almost all CDF regions. It should be remarked that the performance of the proposed method D) is superior to that of cooperative MUMIMO E) except in the central CDF region. Since the proposed method using FFR is still influenced by the frequency resource division, its performance is not as significant as that of cooperative MU-MIMO with single frequency reuse. The performance in the high and low CDF regions achieving the large improvement mainly reflects those of SSs located around the cell-center and cell-edge, respectively. In case of cooperative MU-MIMO, some SSs in adjacent cells are sometimes located very close together and this results in high correlation of the channel vector. This causes a large orthogonalization loss for MU-MIMO beamforming and degrades the spectral efficiency. Applying FFR can avoid such high-correlation situations and makes the performance of the proposed method better. For SSs around the cell-edge region, FFR yields good SNR by increasing the transmission power per sub-channel as well as suppressing ICI. With regard to SSs around the cell-center region, their SINR is kept higher. These characteristics ensure the requirement of the proposed method in (4). This is the reason why our method
Conclusion
In this paper, we proposed applying our ICI cancellation method to FFR in cooperative BS systems. FFR can ensure the conditions under which the ICI cancellation method can work most effectively. A computer simulation showed that the proposed method can achieve large spectral efficiency improvement especially in the high and low CDF regions. Moreover, the average spectral efficiency of the proposed method can match that of cooperative MU-MIMO, which can completely remove ICI. Our ICI cancellation method requires only simple linear processing of the transmission signals resulting in much lower computational load than conventional MU-MIMO processing. Our proposal is a practical approach for system implementation. This paper assumed perfect CSI estimation. Performance with imperfect CSI will be investigated in detail and discussed in the future. References [1] 802.16TGe-2005 Standard: Physical and Medium Access Control Layers for Combined Fixed and Mobile Operation in Licensed Bands, Feb. 2006. [2] 3GPP TS36.300, “Evolved universal terrestrial radio access (EUTRA) and evolved universal terrestrial radio access network (EUTRAN); Overall description.” [3] S. Shamai and B. Zaidel, “Enhancing the cellular downlink capacity via co-processing at the transmitting end,” Proc. VTC’01 Spring, pp.1745–1749, May 2001. [4] 3GPP TR 36.814 V9.0.0, “Further advancements for E-UTRA physical layer aspects,” March 2010. [5] Q.H. Spencer, C.B. Peel, A.L. Swindlehurst, and M. Haardt, “An introduction to the multi-user MIMO downlink,” IEEE Commun. Mag., vol.42, no.10, pp.60–67, Oct. 2004. [6] K. Maruta, T. Maruyama, A. Ohta, and M. Nakatsugawa, “Inter-
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cluster interference canceller for multiuser MIMO distributed antenna systems,” Proc. PIMRC’09, Sept. 2009. [7] K. Maruta, T. Maruyama, A. Ohta, J, Mashino, and M. Nakatsugawa, “Improving spectral efficiency of multiuser-MIMO distributed antenna systems by inter-cluster interference cancellation,” Proc. APMC’10, Dec. 2010. [8] 3GPP; Huawei, “Soft frequency reuse scheme for UTRAN LTE,”
R1-050507, May 2005. [9] ITU-R Recommendation, M. 1225, “Guidelines for evaluation of radio transmission technologies for IMT-2000,” 1997. [10] Q.H. Spencer, A.L. Swindlehurst, and M. Haardt, “Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels,” IEEE Trans. Commun., vol.52, no.2, pp.461–471, Feb. 2004.
