Research Article Coordinated Semidirectional Distributed Antenna System with Capacity and Energy Efficiency Analyses for Cloud Cellular Network

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Research Article

Coordinated Semidirectional Distributed Antenna

System with Capacity and Energy Efficiency Analyses for

Cloud Cellular Network

Xiaodong Xu, Chengjin Luo, Ya Liu, Xiaofeng Tao, and Ping Zhang

National Engineering Laboratory for Mobile Network Security, Beijing University of Posts and Telecommunications, Beijing 100876, China

Correspondence should be addressed to Xiaodong Xu; xuxiaodong@bupt.edu.cn Received 5 June 2015; Revised 27 November 2015; Accepted 6 January 2016 Academic Editor: Giuseppe Mazzarella

Copyright © 2016 Xiaodong Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In order to further explore the coordination gain from the cloud cellular network, the Coordinated Semidirectional Distributed Antenna System (CS-DAS) is proposed with deploying 180-degree sector antennas. Based on the CS-DAS, the coordinated cellular deployment structure is established with corresponding communication procedure designs. The handover process for CS-DAS is designed with less handover rate and signaling overheads. The system performances of ergodic capacity and Energy Efficiency are derived, with a strong focus on the downlink performances, and analyzed with comparisons of current cellular structure. The numerical expressions of ergodic capacity are obtained with improvements of coordinated gain. The Energy Efficiency with different transmission modes is also investigated. The simulation results verify the performance improvements.

1. Introduction

With increasing demands for versatile mobile data services, the mobile communication systems are triggered to further evolve toward much higher data rates and user consistent experiences on both the cell center and cell edge. Mean-while, since the Information and Communication Technol-ogy (ICT) is playing an increasing role in global greenhouse gas emissions, higher Energy Efficiency (EE) should also be focused on along with the capacity booming requirements for future mobile communication systems [1].

In order to fulfill the above requirements, Coordinated Multipoint (CoMP) transmission/reception technique was implemented in Long Term Evolution-Advanced (LTE-A) system as a typical application of coordinated communi-cation techniques. CoMP is proved to provide higher data rates and better cell edge performances [2, 3]. With the aid of CoMP, the EE performance could also be improved by the coordinated transmission and reception with utilizing diversity gains.

Furthermore, the Remote Radio Head (RRH) was also introduced into the CoMP with more flexible cellular deploy-ments, which can fully explore the capacity improvement

from coordination transmissions [2]. The antennas could be deployed remotely from the Base Stations (BSs) with only handling the wireless signal transmission/reception, while the baseband unit of BSs could focus on the centralized signal processing, resource managing and scheduling, and so forth with the cloud computing techniques. Then, the cloud cellular network concepts are proposed, among which the Cloud-infrastructure Radio Access Network (C-RAN) architecture is the representative approach [4]. C-RAN aggregates the resources in the RAN through the centralized management manner with the Virtual BS Pool. The Radio Frequency fronts are deployed with connections to the Virtual BS Pool in a distributed way. The centralized resource allo-cation and scheduling for the users are supported, which makes the optimization of wireless networking strategies easier. There are years of research and trial network tests with the C-RAN, by which the advantages are already verified.

The distributed remote antennas in the C-RAN provided the possibilities for further exploring the coordination gain, but the challenges of how to deploy the distributed remote antenna for maximizing the system capacity and EE also appeared. Therefore, the cellular deployment structure for

Volume 2016, Article ID 8042871, 9 pages http://dx.doi.org/10.1155/2016/8042871

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should be further researched.

The basic distributed and coordinated topology for the cellular network should be the Distributed Antenna Systems (DAS) proposed in 1987 with the fixed cellular structures [5]. The distributed cellular deployments have been evolved in decades with Group Cell Architecture [6], Distributed Wire-less Communication System (DWCS) [7], and also CoMP system. Both the omnidirectional antenna and the sector antenna were researched within the distributed network deployments for obtaining better capacity performances.

These studies have identified potential advantages of DAS such as reduced transmit power, lower handover ratio, and increased system capacity. But the design for the coordinated cellular network structure is the key issue for the distributed network deployment, which also impacts the handover pro-cess in the coordinated distributed networks. Currently, 120-degree sector antennas, that is, antennas with a horizontal coverage of 120∘, are employed in the system for higher frequency reuse and system capacity. But the 120-degree sector antenna also causes more sector-edge effects. However, there is little concern on the deployment of other types of sector antennas in the mobile communication networks.

Actually, the 180-degree sector antenna has been utilized in radar and satellite communication systems (more infor-mation could be found in [8–10]). For the real hardware products, the antenna gain of 180-degree sector antenna is around 15 dBi [10]. With the introduction of 180-degree sector antenna into the cloud based cellular networks, the horizontal coverage features of 180-degree sector antenna will contribute to the decrease of cross-coverage in the cell edge. The handover process could also get benefits from that. Moreover, the coordinated gain brought by the distributed deployment of 180-degree sector antenna will be further improved, also with system EE performances.

Therefore, we proposed the Coordinated Semidirectional Distributed Antenna System (CS-DAS) with 180-degree sec-tor antennas, which will establish better coordinated environ-ments. The main contributions of this paper are as follows:

(i) The CS-DAS is designed for further exploring the coordinated gain in cloud cellular networks with centralized processing.

(ii) The handover procedures in the CS-DAS are provided with better support of user mobility in coordinated networks, which could alleviate frequent handovers and decrease the signaling overhead during the han-dover process.

(iii) The ergodic capacity for downlink scenarios of the CS-DAS is improved further with the coordinated gain in the distributed deployments.

(iv) The system Energy Efficiency with different transmis-sion modes for the downlink CS-DAS is derived. The rest of this paper is organized as follows. The system model with the typical deployment scenario and features of the CS-DAS are described in the next section. In Section 3, the ergodic capacity and EE performances are provided with the statistical expressions derivation. Section 4 presents the

BS₆ BS₁ BS₂ BS₃ BS₅ BS₄ BS₀ 6 A1 A2 A3 A4 A5 A0 A6,0 A1,0 A2,0 A3,0 A4,0 A5,0 A0,6 A0,5 A0,4 A0,3 A0,2 A0,1

Figure 1: The typical cellular deployment scenario with CS-DAS.

performance evaluation with simulation results. Finally, there comes the conclusion.

2. System Model

The typical distributed cellular deployment scenario with DAS is shown in Figure 1. Based on the designed CS-DAS architecture, each cell consisted of one Base Station (BS) at the cell center, which is separated with one Central Antenna Unit (CAU) and six Remote Antenna Units (RAUs) located at the cell edge. The signal processing functions are implemented by the BS with a centralized manner, while the antenna units (AUs) mainly charge the wireless signal transmission/reception via dedicated bidirectional backhauls (e.g., optical fibers) with the BS. This is a small scale cloud cellular structure. If all of the BSs are connected to one Virtual BS Pool, there becomes the typical C-RAN deployment scenario.

The CAU is located at the cell center and deployed with the omnidirectional antenna, while the RAUs are located at the boundary to the adjacent cells and deployed with 180-degree semidirectional sector antennas which are only able to transmit and receive signal at 180-degree horizontal coverage towards the adjacent cells.

For example, BS₀ in Figure 1 has the CAU named 𝐴₀ and six RAUs named 𝐴_0,𝑗. The RAU 𝐴_0,1 is located at the boundaries of BS₀and BS₁with the semidirectional antenna towards the center of BS₁, which creates the cross-coverage area for coordinated transmissions inside of the coverage of CAU𝐴₁ in BS₁. Meanwhile, the RAU𝐴_1,0, which belongs to BS₁, is also located at the boundaries of BS₁ and BS₀ with the semidirectional antenna towards the center of BS₀. There will exist cross-coverage areas, which are potential for coordinated transmissions. The actual covering region for

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BS₁ BS₂ BS₀ A1 A1,2 A2,1 A2 A2,3 A0 A0 A1,0 A1,0 A1,6 A2,0 A2,0 A0,6 A0,5 A0,4 A0,3 A0,2 A0,1 UE₁ UE₁ UE₂ UE₂

Figure 2: Examples of coordinated transmission for the UE.

the BS in the CS-DAS is expanded and the cell edge will be overlapped with two or three AUs which belong to different BSs.

The symbols𝑖and𝑗of the RAU𝐴_𝑖,𝑗represent the relations of the RAU with its belonging BS and location. The symbol𝑖 denotes that the RAU𝐴_𝑖,𝑗 belongs to BS_𝑖and the symbol𝑗 means the coverage region of𝐴_𝑖,𝑗is located inside BS_𝑗.

In order to get better understanding of the CS-DAS cellular deployment structure, Figure 2 is plotted with the examples that support the coordinated communications for users. Three BSs are involved in the coordinated communi-cations with the User Equipment (UE). As shown in Figure 2, UE₁ is locating at the cross-coverage region of the CAU

𝐴0 of BS0 and the RAU 𝐴1,0 of BS1. The coordinated

communication can be established between the two BSs. While UE₂is locating at the cross-coverage region of the CAU

𝐴₀of BS₀, the RAU𝐴_1,0of BS₁, and also the RAU𝐴_2,0of BS₂, the CoMP with three BSs will be set up for UE₂. The cell edge performance will be further improved.

The resources coordination for the UE will be handled by the centralized processing BSs via CoMP techniques. The RAU’s resource usage will have constraints from the adjacent cells at which the RAU actually locates to avoid the interference. The current intercell interference coordination solutions, such as Fractional Frequency Reuse (FFR) and Soft Frequency Reuse (SFR) implemented in LTE networks, can still be applied with modifications for the CS-DAS architecture.

As shown in Figure 1, because all the RAUs are distributed within the coverage areas in adjacent cells, the frequency allocation for the reusing policy is different with current FFR or SFR schemes. For example, the RAU𝐴_0,1is located at the boundaries of BS₀and BS₁with the semidirectional antenna towards the center of BS₁, which creates the cross-coverage area for coordinated transmissions inside of the coverage of CAU𝐴₁in BS₁. So, the frequency allocated to the RAU𝐴_0,1 for reusing should be from the available frequency set of BS₁ rather than the available frequency set of its connected BS₀.

Furthermore, this frequency reuse method could also guar-antee the coordinated communication between RAU 𝐴_0,1 and CAU𝐴₁, because they are reusing the same frequency set of BS₁. The frequency reuse policy for the CS-DAS structure is worth to be further researched in the future, which could bring more benefits to this architecture.

Based on the deployment rules, the CS-DAS architecture can bring more benefits besides the coordinated transmis-sions. With more and more antennas deployed inside of the cellular network, the handover will be more frequent, which will degrade both the user experiences and the network performances. But thanks to the coordinated coverage areas created by the CS-DAS, there will be less handovers and the moving users’ experiences will be improved, while the network performances will also be guaranteed with less signaling overheads associating the handovers.

In order to show the benefits brought by the CS-DAS, a further perspective is given with one application scenario as shown in Figure 3, where the UE performs handover through two adjacent cells (BS₀ and BS₁) and the communica-tion/handover process will be divided into three procedures according to the CS-DAS structure.

Procedure 1. The UE moves from the cell center to the cell

edge of BS₀, where the cell edge or cell center can be simply determined by the user received Reference Signal Received Power (RSRP). During the UE’s moving inside of BS₀, the UE maintains continuous communication with BS₀from the CAU𝐴₀. When the UE moves into the cell edge of BS₀, the UE will additionally get access to BS₁ with the RAU 𝐴_1,0 acting as the CoMP transmission point. When UE’s access to BS₁is accomplished, the UE will get service from both BS₀ and BS₁ with two AUs’ coordinated transmission/reception to get performance gain from CoMP.

Procedure 2. The UE moves from the cell edge of BS₀ to

the cell edge of BS₁. The serving AU set will consist of𝐴_0,1 from BS₀ and 𝐴₁ from BS₁ instead of the former serving

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Procedure 1:

The UE moves from the

Serving AUs set:

Serving base stations:

The UE can maintain the conversation when it gets connection to the base

Procedure 2: Procedure 3: The UE moves from the

Serving AUs set:

The UE moves from the

Serving AUs set:

The UE disconnects with without interrupting the conversation

center of BS₀to the edge of BS₀

station BS₁

A1,0 A0,1

BS₁ BS₀

edge of BS₀to the edge of BS₁

The serving AU of BS₀ hands over from_A₀to_A_0,1 and AU of BS₁hands over to_A₁

edge of BS₁to the center of BS₁

the base station BS₀

BS₀_{→ (}BS₀_,BS₁₎ A0→ (A0, A1,0) (BS₀,BS₁) → (BS₁,BS₀) (A0, A1,0) → (A0,1, A1) (BS₁,BS₀) →BS₁ (A0,1, A1) → A1

Figure 3: UE handover procedures in CS-DAS.

AU set in Procedure 1 with the CAU𝐴₀ and the RAU𝐴_1,0. Please note that the current serving cells are still BS₀ and BS₁, which means that the handover only occurs inside of the coordinated set. The handovers will be easily handled without any extra overheads.

Procedure 3. The UE moves from the cell edge to the cell

center of BS₁. While the UE moves out of cross-coverage region of the RAU 𝐴_0,1 of BS₀, the coordinated trans-mission/reception will be terminated and the serving AU set will be updated to only 𝐴₁ from BS₁. The handover will be finished with BS₀ withdrawing from the serving cells. BS₁is always involved in the whole handover process from Procedure 2. The UE handover performance will be guaranteed and the signaling exchanges will be less than current handover procedures in LTE systems.

From the procedures given above in the CS-DAS, it can be concluded that when a UE moves from one cell to another, the UE can always stay in communication with at least one BS. The handover processes from BS₀to BS₁achieve the seamless handover function. BS₀will guarantee the UE’s performance until it moves into the cell center of BS₁. And BS₁has already taken parts in the responsibility of serving the UE even from where it still stays in the cell edge of BS₀. The whole procedure just seems like the relay race.

Meanwhile, as analyzed in [11], the rate of handover mainly depends on the relative signal strength differences from adjacent antennas. Based on the CS-DAS, the signal strength of desired RAU is relatively bigger than other undesired CAUs or RAUs at the cell edge (low path-loss region of the desired RAU). The total number of handovers can be decreased. What is more, from the features of 180-degree semidirectional sector antennas, such as the ability of

mitigating Doppler Shift [8], CS-DAS can also be used on highway deployment scenarios and achieve more improve-ments.

3. Ergodic Capacity Analyses for CS-DAS

For the performance evaluation of CS-DAS, the ergodic capacity is one of the most important metrics for cellular deployment structures. In this section, the ergodic capacity for CS-DAS structure will be studied. We mainly focus on the downlink performance in this paper.

The CS-DAS cellular deployment structure used for capacity analysis and evaluation is shown in Figure 2, where UE₁gets access to BS₀through the CAU𝐴₀and BS₁through the RAU𝐴_1,0. The serving AU set consists of{𝐴₀, 𝐴_1,0}. UE₂ gets access to the serving AU set{𝐴₀, 𝐴_1,0, 𝐴_2,0}.

Assume that there are 𝑚cells (𝑀 = 7𝑚 AUs) in the research region. The frequency resource used by UE₁ is assigned as𝑓. As𝑓may be assigned to the cell center user or the cell edge user with𝑛coordinated AUs (CoAU-𝑛,𝑛 = 2 or 3) in BS₁, there are definitely one part of signal power on𝑓 from the CAU𝐴₁and no more than two parts of signal power on𝑓from the RAUs𝐴_1,𝑖.

Generally, we can deduce the common cases that there will be one part of signal power from the CAU and no more than two parts of signal power from the RAUs of adjacent cells. Thus, there are totally no more than3𝑚parts of signal power on𝑓for the users in the research area.

The discrete-time received signal formula for the analyzed UE is given as

𝑦 =∑𝑀

𝑖=1

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where𝑤_𝑖is an indicator factor that represents whether there exists signal power on𝑓from the AU𝑖or not (i.e.,𝑤_𝑖 = 0 or 1) and∑𝑀_𝑖=1𝑤_𝑖 ≤ 3𝑚. 𝑆_𝑖 denotes the long term shadow fading modeled by log-normally distributed random variable with standard deviation𝜎and mean value𝜇_𝑖, with both being in dB. The mean value is defined as𝜇_𝑖 = 10log₁₀(𝑑_𝑖/𝑑₀)−𝛼 [12], with the path-loss exponent𝛼, constant𝑑₀, and distance

𝑑_𝑖 between the AU 𝑖 and the UE. ℎ_𝑖 denotes the gain of the frequency flat Rayleigh fading channel, modeled by independent and identically distributed complex Gaussian variable with unit varianceℎ_𝑖 ∼ 𝑁(0, 1). 𝑥_𝑖 represents the signal transmitted from the AU𝑖and𝑧is the additive noise.

Let𝐷and𝑈denote the sets of indices representing the coordinated AUs and other remaining AUs. Equation (1) can be rewritten as

𝑦 = ∑

𝑖∈𝐷√𝑆𝑖ℎ𝑖𝑥𝑖+ ∑𝑗∈𝑈𝑤𝑗√𝑆𝑗ℎ𝑗𝑥𝑗+ 𝑧. (2)

The UE received signal power is

𝐸 [󵄨󵄨󵄨󵄨𝑦󵄨󵄨󵄨󵄨2_{] = ∑} 𝑖∈𝐷 𝑆_𝑖󵄨󵄨󵄨󵄨ℎ_𝑖󵄨󵄨󵄨󵄨2_{𝐸 (󵄨󵄨󵄨󵄨𝑥}_𝑖󵄨󵄨󵄨󵄨2) + ∑ 𝑗∈𝑈 𝑤_𝑗𝑆_𝑗󵄨󵄨󵄨󵄨_󵄨ℎ_𝑗󵄨󵄨󵄨󵄨_󵄨2_{𝐸 (󵄨󵄨󵄨󵄨󵄨𝑥}_𝑗󵄨󵄨󵄨󵄨_󵄨2) + 𝜎2_𝑧, (3)

where𝑃_𝑖= 𝐸(|𝑥_𝑖|2)is the average transmit signal power of the AU𝑖,𝑌_𝑖 = 𝑆_𝑖|ℎ_𝑖|2𝑃_𝑖represents the desired𝑖th part of signal power, and𝑤_𝑗𝑌_𝑗 = 𝑤_𝑗𝑆_𝑗|ℎ_𝑗|2𝑃_𝑗denotes the undesirable𝑗th part of signal power (i.e., the interference).

For simplicity of the capacity analyses, we mainly con-sider the path-loss effects during the ergodic capacity analysis for both the CS-DAS and traditional cellular network. Then, the relationship between Signal to Interference plus Noise Ratio (SINR) and planar position can be expressed as one-to-one map and the ergodic capacity can be calculated as [13]

𝐶AVG= ∬

𝑆𝑝 (𝑥, 𝑦)log2(1 +SINR(𝑥, 𝑦)) 𝑑𝑥 𝑑𝑦, (4)

where𝑆is the coverage area of one cell in the CS-DAS,𝑝(𝑥, 𝑦) is the Probability Density Function (PDF) of UE located at position(𝑥, 𝑦), and SINR(𝑥, 𝑦)is the function of SINR. Because the coordinated communication mode is embedded in CS-DAS architecture, we cannot obtain the closed-form capacity with interference considered. Therefore, we choose the integral capacity expressions as (4) for conducting the evaluations on capacity and EE performance improvements brought by the CS-DAS architecture.

4. Energy Efficiency Analyses for CS-DAS

According to the coordinated communications implemented in the CS-DAS, the downlink Energy Efficiency performances of the cell edge users served with the coordinated AU set will be the focus. Due to many previous research works, the EE performance of users at the cell center served only by one CAU scenario will not be of concern in this part.

During the following analyses, we assume the system is interference-limited; thus the effect of noise is negligible.

The instantaneous SIR of UE with CoAU-𝑛 coordinated transmission mode can be written as

𝛾𝑛= ∑ 𝑛 𝑖=1𝑌𝑖

∑𝑀_𝑗=𝑛+1𝑌𝑗

. (5)

EE is defined as the ratio of achieved transmission rate over the total power consumption, which is given as

𝜂_𝑛= log2(1 + 𝛾𝑛)

∑𝑛_𝑗=1𝑃_𝑗+ 𝑃_𝐶, (6)

where 𝑃_𝑗 is the transmit power of the 𝑗th coordinated AU and 𝑃_𝐶 is the circuit power consumption which has been discussed in [14]. For simplicity, the circuit power consumption is defined as a constant𝑃_𝐶 = 0.2W (given in [15]) in the following analyses.

The Cumulative Distributed Function (CDF) of EE𝜂_𝑛can be obtained as

𝐹_𝜂_𝑛(𝜂) = ∫∞

0 ⋅ ⋅ ⋅ ∫ ∞

0 𝐹𝜂𝑛|S𝑀(𝜂) 𝑓S𝑀(𝑠) 𝑑𝑠, (7)

where S_𝑀 denotes the received signal vectors, S_𝑀 =

[𝑆₁𝑆₂⋅ ⋅ ⋅ 𝑆_𝑀], and𝐹_𝜂_𝑛_|_S𝑀(𝜂)represents the conditional CDF of EE𝜂_𝑛 conditioned onS_𝑀. And the joint PDF ofS_𝑀can be obtained in [16] 𝑓S𝑀(𝑠) =∏𝑀 𝑖=1 {10/ln(10) √2𝜋𝜎𝑆_𝑖 exp(− (10log₁₀𝑆_𝑖− 𝜇_𝑖)2 2𝜎2 )} . (8)

The EE performances of different scenarios as two AUs and three AUs involved in the coordinated transmission will be analyzed separately.

Scenario 1(CoAU-2, coordinated transmission with 2 AUs).

As shown in Figure 2, UE₁is in CoAU-2 transmission mode. For simplicity of analyses, only the main interference will be considered during the following analyses. The interference for UE₁mainly comes from the adjacent cells, which are the CAUs of BS₁and BS₂, also with the RAUs inside of BS₁due to their beam directions. Thus, the SIR for UE₁can be written as 𝛾UE1 = 𝑌₀+ 𝑌_1,0 ∑2_𝑖=1𝑌_𝑖+ ∑6_𝑖=1𝑤_𝑖,1𝑌_𝑖,1+ 𝜎2 𝐼UE1 , ₍₉₎

where 𝑤_𝑖,1 is Boolean and ∑6_𝑖=1𝑤_𝑖,1 ≤ 2 with the coor-dinated AU set establishment rules described in Section 2.

𝜎2

𝐼UE1 represents the other remaining interference modeled

by its expected value and 𝜎_𝐼2_UE

1 = ∑

𝑀

𝑖=3𝑃𝑖(𝑑𝑖/𝑑0)−𝛼 +

∑𝑀_𝑗=3∑6_𝑖=1𝑤_𝑖,𝑗𝑃_𝑖,𝑗(𝑑_𝑖,𝑗/𝑑₀)−𝛼_[17].

If∑6_𝑖=1𝑤_𝑖,1 = 0, the SIR in (9) will be maximum and is given as 𝛾UE1= 𝛾 max UE1 = 𝑌₀+ 𝑌_1,0 𝑌₁+ 𝑌₂+ 𝜎2 𝐼UE1 . (10)

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of𝑌_𝑖and can be obtained in the actual networks. For given values of log-normal shadowing variable 𝑆_𝑖, 𝑌_𝑖 follows the Chi-squared distribution with 2 degrees of freedom. And𝑌_𝑖 follows the exponential distribution conditioned on𝑆_𝑖 and the PDF is𝑓_𝑌_𝑖_|𝑆_𝑖(𝑢) = (1/𝑆_𝑖𝑃_𝑖)exp(−𝑢/𝑆_𝑖𝑃_𝑖), where𝑢 > 0.

The numerator part of (10) 𝑌num = 𝑌0 + 𝑌1,0 follows

the weighted Chi-squared distribution conditioned on𝑆₀and

𝑆1,0, based on the sum principle of two independent random

variables [18]; the corresponding PDF can be derived as

𝑓_𝑌_num_|𝑆₀_,𝑆_1,0(𝑢) = exp(−𝑢/𝑆0𝑃0) −exp(−𝑢/𝑆1,0𝑃1,0) 𝑆₀𝑃₀− 𝑆_1,0𝑃_1,0 , (11)

where𝑢 > 0.

Similarly, the denominator of (11) is𝑌den= 𝑌1+𝑌2+𝜎𝐼2UE1

and its conditional PDF is given as

𝑓𝑌den|𝑆1,𝑆2(𝑢) =exp(− (𝑢 − 𝜎 2 𝐼UE1)/𝑆1𝑃1) −exp(− (𝑢 − 𝜎 2 𝐼UE1)/𝑆2𝑃2) 𝑆1𝑃1− 𝑆2𝑃2 , (12) where𝑢 > 𝜎_𝐼2_UE 1.

According to the transformation rules given in [18], the conditional PDF 𝑓_𝛾max

UE1|SmaxUE1(𝛾) =

∫_𝜎∞2

𝐼UE1𝑓𝑌num|𝑆0,𝑆1,0(𝛾𝑢)𝑓𝑌den|𝑆1,𝑆2(𝑢)𝑢 𝑑𝑢

will be obtained. And the conditional CDF is given as

𝐹_𝛾max UE1|SmaxUE1(𝛾) = ∫ 𝛾 −∞𝑓𝛾UEmax1|SmaxUE1(𝑢) 𝑑𝑢 = 1 − 𝜌03exp(−𝛾/𝜌0) (𝜌₀− 𝜌_1,0) (𝜌₁𝛾 + 𝜌₀) (𝜌₂𝛾 + 𝜌₀) − 𝜌 3 1,0exp(−𝛾/𝜌1,0) (𝜌1,0− 𝜌0) (𝜌1𝛾 + 𝜌1,0) (𝜌2𝛾 + 𝜌1,0), (13) where𝜌_𝑖= 𝑆_𝑖𝑃_𝑖/𝜎2_𝐼_UE 1,𝜌𝑖,𝑗= 𝑆𝑖,𝑗𝑃𝑖,𝑗/𝜎 2 𝐼UE1, andS max UE1 = [𝑆0, 𝑆1, 𝑆₂, 𝑆_1,0].

Similarly, by defining𝜆₀= 𝜌₀,𝜆₁ = 𝜌_1,0. The conditional CDF𝐹_𝛾

UE1|SUE1(𝛾)can be obtained as

𝐹_𝛾_UE 1|SUE1(𝛾) = 1 −∑1 𝑖=0 𝜆9 𝑖exp(−𝛾/𝜆𝑖) (𝜆_𝑖− 𝜆_𝑖mod2+1) 𝐺0(𝜆𝑖) 𝐺1(𝜆𝑖), (14) where𝐺₀(𝜆_𝑖) = ∏1_𝑗=0(𝜌_𝑗𝛾+𝜆_𝑖)and𝐺₁(𝜆_𝑖) = ∏6_𝑗=1(𝑤_𝑗,1𝜌_𝑗,1𝛾+ 𝜆_𝑖).

The EE for CoAU-2 (UE₁) is given as𝜂_UE₁ = log₂(1 +

𝛾UE1)/(𝑃0+ 𝑃1,0+ 𝑃𝐶); thus

𝐹_𝜂_UE

1|SUE1(𝜂) = 𝐹𝛾UE1|SUE1(2

(𝑃0+𝑃1,0+𝑃𝐶)𝜂− 1) . ₍₁₅₎

By combining (7), (8), (13), (14), and (15), the CDF𝐹_𝜂max

UE1(𝜂)

and𝐹_𝜂_UE

1(𝜂)will be obtained.

As shown in Figure 2, UE₂is in CoAU-3 transmission mode. Similarly, the SIR for UE₂can be written as

𝛾UE2= 𝑌₀+ 𝑌_1,0+ 𝑌_2,0 ∑2_𝑖=1𝑌_𝑖+ ∑6_𝑖=1𝑤_𝑖,1𝑌_𝑖,1+ ∑6_𝑗=1𝑤_𝑗,2𝑌_𝑗,2+ 𝜎2 𝐼UE2 , ₍₁₆₎ where𝜎2_𝐼_UE 2= ∑ 𝑀 𝑖=3𝑃𝑖(𝑑󸀠𝑖/𝑑0)−𝛼+∑𝑀𝑗=3∑6𝑖=1𝑤𝑖,𝑗𝑃𝑖,𝑗(𝑑󸀠𝑖,𝑗/𝑑0)−𝛼, ∑6_𝑖=1𝑤_𝑖,1≤ 2, and∑6_𝑗=1𝑤_𝑖,2≤ 2.

Similar to the analyses of scenario CoAU-2, by defining

𝜆₀ = 𝜌₀,𝜆₁ = 𝜌_1,0, and𝜆₂ = 𝜌_2,0, the conditional CDF

𝐹_𝛾_UE

2|SUE2(𝛾)can be derived as

𝐹_𝛾_UE 2|SUE2(𝛾) = 1 − 2 ∑ 𝑖=0 𝜆16 𝑖 exp(−𝛾/𝜆𝑖) 𝐺₀(𝜆_𝑖) 𝐺₁(𝜆_𝑖) 𝐺₂(𝜆_𝑖) 𝐺₃(𝜆_𝑖), (17) where𝐺₀(𝜆_𝑖) = ∏2_{𝑗=0,𝑗 ̸=𝑖}(𝜆_𝑖− 𝜆_𝑗),𝐺₁(𝜆_𝑖) = ∏2_𝑗=1(𝜌_𝑗𝛾 + 𝜆_𝑖), 𝐺₂(𝜆_𝑖) = ∏6_𝑗=1(𝑤_𝑗,1𝜌_𝑗,1𝛾 + 𝜆_𝑖), and𝐺₃(𝜆_𝑖) = ∏6_𝑗=1(𝑤_𝑗,2𝜌_𝑗,2𝛾 + 𝜆_𝑖).

The EE for CoAU-3 (UE₂) is given as𝜂_UE₂ = log₂(1 +

𝛾UE2)/(𝑃0+ 𝑃1,0+ 𝑃2,0+ 𝑃𝐶); thus

𝐹_𝜂_UE

2|SUE2(𝜂) = 𝐹𝛾UE2|SUE2(2

(𝑃0+𝑃1,0+𝑃2,0+𝑃𝐶)𝜂− 1) . ₍₁₈₎

By combining (7), (8), and (17) with (18),𝐹_𝜂_UE

2(𝜂)can also

be obtained.

For comparisons, based on the traditional cellular struc-ture without coordinated transmission as the baseline, the users will get service from only one CAU. The ergodic capacity of the traditional cellular structure still follows the same formula form as (4), but the interference from the RAUs will not exist. The SIR for UE₁and UE₂can be expressed in the unified form and written as𝛾_𝑐 = 𝑌₀/(𝑌₁+ 𝑌₂+ 𝜎2_𝐼). The conditional CDF of EE can be derived as

𝐹_𝜂_𝑐_|_S𝑐(𝜂) = 1 − 𝜌 2 0exp(− (2(𝑃0+𝑃𝐶)𝜂− 1) /𝜌0) (𝜌0− 𝜌1+ 𝜌12(𝑃0+𝑃𝐶)𝜂) (𝜌0− 𝜌2+ 𝜌22(𝑃0+𝑃𝐶)𝜂), (19)

whereS_𝑐 = [𝑆₀, 𝑆₁, 𝑆₂]and𝜎2_𝐼 = ∑𝑀_𝑖=3𝑃_𝑖(𝑑_𝑖/𝑑₀)−𝛼.𝐹_𝜂_𝑐(𝜂)for UE₁and UE₂can be derived with formulas (7), (8), and (19).

5. Performance Evaluations

In this section, the performance evaluation with simulation results for both the downlink ergodic capacity and EE is conducted, and the comparison with traditional cellular structure will be introduced.

Simulations are operated for the CS-DAS and traditional cellular structure under the same conditions. A general 3-layer cellular structure with 19 BSs is considered in the simulation. The simulation parameters and settings are listed in Table 1 based on 3GPP evaluation model [2]. Because

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Table 1: Simulation parameters and settings.

Parameters Settings

ISD 500 m

Antenna gain of 180-degree sector antenna 15 dBi [10]

Antenna gain of omnidirectional antenna 5 dBi [2]

Location of UE₁ (3𝑅/4, √3𝑅/8)

Location of UE₂ (3𝑅/4, 𝑅/16)

Path-loss model PL(𝑑) = 128.1 + 37.6log₁₀𝑑

𝑃CAU 46 dBm

𝑃RAU 𝑃RAU= 𝑃CAU−PL(𝑅) +PL(𝑅/2)

we mainly focus on the sector antenna’s horizontal coverage capabilities for multicell coordination, the vertical coverage features are not involved in the simulation. The relationship between the average transmit power of CAU (𝑃CAU) and RAU

(𝑃_RAU) is shown as𝑃RAU= 𝑃CAU−PL(𝑅) +PL(𝑅/2)with the

consideration to make the same attenuation with the path loss at the coverage boundary.

Because there are two coordination modes above for the coordinated communications, in order to analyze the EE of the two modes of two AU coordinated transmissions and three AU coordinated transmissions, we predetermine UE₁and UE₂locations to guarantee the desired coordinated communication mode.

5.1. Simulation Results for Ergodic Capacity. In order to

com-pare the capacity performances of CS-DAS with traditional cellular structure, we define the capacity gain as the capacity difference to the traditional cellular structure capacity ratio, given as

Gain= (𝐶CS-DAS− 𝐶traditional)

𝐶traditional

, (20)

where 𝐶CS-DAS is the capacity of CS-DAS and 𝐶Trad is the

capacity of traditional cellular architecture.𝐶CS-DASand𝐶Trad

can be obtained from formula (4) in Section 3.

The influences of intersite distance (ISD) and the average transmit power of CAU are both considered in the ergodic capacity simulation, and the result is shown in Figure 4. It can be found that the least gain of CS-DAS is about 22.08% and the difference between maximum and minimum gains is less than 0.26% (the maximum is 22.34%) which means that CS-DAS can almost bring the same capacity gain in different deployment scenarios with different ISDs or transmission powers.

In order to show the performance especially in the cell edge with coordinated gain, the CDF of the ergodic capacity for CS-DAS and traditional cellular structure are evaluated and the results are shown in Figure 5. The whole throughput performance of CS-DAS is better than the traditional cellular structure as shown in Figure 4. The cell edge throughput performance (5% of the CDF) is further better with the CS-DAS.

5.2. Simulation Results for Energy Efficiency. During this

subsection, simulations of the EE are performed for UE₁ and UE₂with different coordination transmission scenarios

46 41 36 31 26 21 200 400 600 800 1000 200 400 600 Power ( dBm) ISD (m) 22.1 22.2 22.3 22.4 C apaci ty ga in (%)

Figure 4: Capacity gain of CS-DAS over traditional cellular struc-ture. CS-DAS Traditional 200 400 600 800 1000 1200 1400 0 Throughput (bps) 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 C u m u la ti ve di st ri b u tio n fun ctio n

Figure 5: CDF of the ergodic capacity.

introduced in Section 4. The simulation is carried out by taking both path loss and Rayleigh fading with the same parameter setting as Table 1.

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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 C u m u la ti ve di st ri b u tio n fun ctio n 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2 0 EE (bps/Hz/W) F𝜂𝑐(𝜂) F𝜂max(𝜂) F𝜂_3,2(𝜂) F𝜂4,1(𝜂) F𝜂6,2(𝜂) F𝜂6,1(𝜂) F𝜂2,2(𝜂) F𝜂3,1(𝜂) F𝜂_1,2(𝜂) F𝜂1,1(𝜂) F𝜂2,1(𝜂) 𝜂_c 𝜂_3,1 𝜂_1,1 𝜂_2,1 𝜂_4,1 𝜂_6,1 𝜂_1,2 𝜂_2,2 𝜂_6,2 𝜂_3,2 𝜂max

Figure 6: EE distributions for CS-DAS with CoAU-2 transmission scenario and traditional cellular structure.

Scenario 1(CoAU-2). The simulation is performed on UE₁

with CoAU-2 coordinated transmission scenario. And the traditional cellular structure transmission with only one CAU serving UE₁ is also simulated for comparison. For CoAU-2 coordinated transmission scenario, as shown in Figure CoAU-2, the coverage direction of the RAU𝐴_0,1 is opposite to UE₁;

𝑤_0,1 = 0is established. For the situation that the interfering signal power from BS₁is just one part (i.e.,∑5_𝑖=1𝑤_𝑖,1= 1), the EE is indexed as𝜂_𝑖,1(𝑖 = 1, . . . , 5);𝑖represents the number of RAUs from which the interference comes. Meanwhile, on the situation that the interfering signals from the RAUs of BS₁ have two parts (i.e.,∑5_𝑖=1𝑤_𝑖,1 = 2), which means the same resource𝑓is allocated for 3-AU coordination transmission mode with two adjacent RAUs and one CAU (the numbers of the adjacent RAUs should be𝑖and𝑖mod6 + 1), the EE for different interference sources are indexed as𝜂_𝑖,2 (𝑖 = 1, . . . , 5) when𝑤_𝑖,1=boolean(𝑖 − 5)and𝑤_𝑖_mod_6+1,1=boolean(𝑖mod

6 + 1 − 5).

Derived from the above expression, we can get that𝜂_4,1=

𝜂_4,2and𝜂_6,1 = 𝜂_6,2; the EE for UE₁ can totally be expressed as 10 results with different interference resources (including

𝜂_max, where∑6_𝑖=1𝑤_𝑖,1= 0).

The CDFs of the EE 𝜂_𝑐,𝜂_𝑖,0,𝜂_𝑖,1, and𝜂_max are obtained by using the derived equations for the CoAU-2 scenario and the traditional cellular structure in Section 4. The results are plotted in Figure 6. The more right position the curve lies in, the better performance it indicates. Demonstrated by the results, the EE performances of CoAU-2 scenario are much better than the traditional cellular structure and the best situation of CoAU-2 (𝛾_UE₁ = 𝛾_UEmax

1) produces the most

improved EE performance with𝜂_max. The sorted right-left

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 C u m u la ti ve di st ri b u tio n fu n ctio n 0.02 0.04 0.06 0.08 0.1 0.12 0 EE (bps/Hz/W) F𝜂𝑐(𝜂) F𝜂max(𝜂) 𝜂c 𝜂0,1 𝜂0,2 𝜂1,0 𝜂1,1 𝜂1,2 𝜂2,0 𝜂2,1 𝜂2,2 𝜂max

Figure 7: EE distributions for CS-DAS with CoAU-3 transmission scenario and traditional cellular strucutre.

order of𝐹_𝜂_𝑖,2(𝜂)and𝐹_𝜂_𝑖,1(𝜂)is given as𝐹_𝜂_2,1(𝜂),𝐹_𝜂_1,1(𝜂),𝐹_𝜂_3,1(𝜂),

𝐹_𝜂_1,2(𝜂),𝐹_𝜂_2,2(𝜂),𝐹_𝜂_6,1(𝜂),𝐹_𝜂_6,2(𝜂),𝐹_𝜂_4,1(𝜂), and𝐹_𝜂_3,2(𝜂). Actually, the lower the interferenceUE₁suffered from the interfering RAU, the better EE performance will be gotten.

Furthermore, taking a close eye on the curve of𝐹_𝜂_𝑖,1(𝜂), the sorted right-to-left order is given as 𝐹_𝜂_2,1(𝜂), 𝐹_𝜂_1,1(𝜂),

𝐹𝜂3,1(𝜂),𝐹𝜂6,1(𝜂), and𝐹𝜂4,1(𝜂), while the distances between the

RAU 𝐴_𝑖,1 and UE₁ are shown as 𝑑_2,1 > 𝑑_1,1 > 𝑑_3,1 >

𝑑_6,1 > 𝑑_4,1, which means the farther from UE₁ to the interfering RAUs, the better EE performance. So, according to this factor, we can further design the resource allocation and intercell interference coordination strategies for better EE performances.

Scenario 2(CoAU-3). The evaluation for the CoAU-3

sce-nario is conducted on UE₂ comparing with the traditional cellular structure. The basic deployment is also shown in Figure 2; the coverage directions of the RAUs 𝐴_0,1, 𝐴_0,2, and 𝐴_1,2 are opposite to UE₂; thus 𝑤_0,1 = 0, 𝑤_0,2 = 0, and 𝑤_1,2 = 0. The interference signals from BS₁ and BS₂ are considered in the simulation, and there may be 0, 1, or 2 parts of interference signals from the above BSs. Totally, there will be 80 possibilities for EE of UE₂. To simplify the simulation results and without loss of the generality, we will fix the RAUs of𝐴_2,1and𝐴_2,3as two main interference sources. By defining𝜂_𝑖,𝑗for the EE with𝑖parts of interference power from BS₁ and 𝑗 parts of interference from BS₂, the simulation result is shown in Figure 7. It can also be con-cluded that the CoAU-3 scenario is better than the traditional cellular structure in terms of EE and 𝜂_max shows the best performance.

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6. Conclusions

This paper proposed the Coordinated Semidirectional Dis-tributed Antenna System to further explore the coordi-nated gain with deploying 180-degree sector antennas in the downlink scenario of cloud cellular networks. With special designed topology of antenna deployments and coordinated antenna set establishment, the new designed handover pro-cedure has advantages of decreasing handover rate and signaling overheads in the coordinated communications. Furthermore, we can get both the capacity gain and Energy Efficiency performance improvements. The ergodic capacity and the Energy Efficiency in the downlink are deduced and analyzed with the numerical expressions. Moreover, the EE performances of given users for different coordinated scenar-ios with CAU and RAUs are derived. The simulation results show that the downlink capacity gain brought by the CS-DAS can be at least 22.08% over the traditional cellular structure. The downlink EE performance improvements in CS-DAS are also identified with different coordinated scenarios by simulations. The CS-DAS gives a new deployment trial for exploring the coordinated gain in centralized cloud cellular networks.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

This paper is supported by the Nature and Science Foun-dation of China under Grants nos. 61471068 and 61421061, Beijing Nova Programme no. Z131101000413030, and Collab-orative Project 2015DFT10160.

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