Two-Stage Cooperative Multicast Transmission with ... - IEEE Xplore

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 32, NO. 12, DECEMBER 2014

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Two-Stage Cooperative Multicast Transmission with Optimized Power Consumption and Guaranteed Coverage Yiqing Zhou, Senior Member, IEEE, Hang Liu, Zhengang Pan, Senior Member, IEEE, Lin Tian, Member, IEEE, Jinglin Shi and Guanghua Yang, Member, IEEE

Abstract—Wireless multicast is a spectrum efficient method for group-data transmission. This paper focuses on energy efficient two-stage cooperative multicast transmissions, aiming to minimize the total transmission power while ensuring a practical coverage ratio. To focus on the relationship between the base station (BS) power at the first stage (PBS,C ) and the total power consumption, a selective combining based on average received signal strength (SCA) is assumed at the receiver and the user density is supposed to be sufficiently high. Then a mobile relay (MR) arrangement based on sector ring structures is proposed for the second stage transmission, followed by an analytical derivation of the optimal PBS,C conditioned on a desired coverage ratio. In addition, further approximations are exploited to provide a simple theoretical estimation for the optimal PBS,C , whose effectiveness is verified by numerical results. It is shown that compared to the conventional one-stage multicast transmission, the proposed two-stage cooperative scheme can reduce the total power consumption and the BS power consumption by more than 40% and 80%, respectively. Although the proposed scheme is obtained based on SCA, when the user density is higher than 2 · 10−4 , a coverage ratio of 95% can be guaranteed by using a practical CP combining with the proposed scheme. Moreover, the effectiveness of the proposed MR arrangement is verified by simulations where it outperforms other three arrangements. It is also shown that targeting at minimizing the total transmission power with guaranteed coverage, the proposed scheme significantly outperforms the existing two-stage scheme in terms of energy consumption and efficiency. Index Terms—optimized power consumption, coverage ratio, multicast transmission, two-stage cooperative transmission, user density.

I. I NTRODUCTION

D

UE to the broadcast transmission nature of radio communications, wireless multicast transmission is known as a spectrum efficient method for group-data transmission. As radio resources become more and more stringent, multicast techniques have drawn a lot of interests and been applied in various systems, such as WiMax with Internet Protocol television (IPTV) [1] and long term evolution (LTE) systems Manuscript received April 15, 2012; revised November 2, 2012. Y. Zhou, H. Liu, L. Tian and J.L. Shi are with Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China (e-mail: {zhouyiqing, liuhang, tianlindd, sjl}@ict.ac.cn). H. Liu is with University of Chinese Academy of Sciences, Beijing, China. Z. Pan is with Green Communication Research Center (GCRC) of China Mobile Research Institute (CMRI), Beijing, China (e-mail: [email protected]). G. Yang is with the department of Electrical and Electronic Engineering, University of Hong Kong, Hong Kong, China (e-mail: [email protected]). Digital Object Identifier 10.1109/JSAC.2014.141208.

with multimedia broadcast multicast service (MBMS) [2][5]. In the conventional wireless multicast scheme, to ensure all mobile stations (MS) receiving the data, the transmission rate is limited by the worst channel condition experienced by all MSs. This results in a saturated system throughput when the number of users increases [6]. Recently, multistage cooperative multicast transmission has been proposed to improve the system performance [7], where the transmission is divided into several stages. This paper focuses on the two-stage scheme since it is more practical. Aiming to maximize the system throughput, two-stage multicast has been investigated in [8], where at the 1st stage, the base station (BS) multicasts data to all MSs, targeting at a relatively low coverage ratio, e.g., 50%. Then at the 2nd stage, all the MSs that successfully receive data at the 1st stage will act as mobile relays (MRs) to forward the data to remaining MSs. With the help of MRs, the system throughput can be improved significantly. However, since all successful MSs are chosen as MRs at the 2nd stage, the required transmission power also increases with the number of MRs, which is not energy efficient. Moreover, two Maximum Ratio Combining (MRC)-based two-stage cooperative multicast schemes are investigated in [9]. It is shown that given a fixed total energy, allocating half of the total transmission power to the BS minimizes the outage probability of the cooperative multicast schemes. Recently, power consumption of wireless networks has attracted a lot of attentions as energy costs make up a vast portion of operational expenditure (OPEX). For example, China Mobile spends more than 40% OPEX on electric energy, among which about 72% is consumed by the BS [10]. Improving power efficiency of wireless networks has become a hot topic in both academia and industry [11]. Cooperative communication is promising to reduce power consumption and a lot of research has been carried out in this area [1215]. In cooperative multicast transmission, a few studies have been conducted to save energy. For example, to employ the cooperative multicast transmission with reasonable power consumption, the nearest neighbor protocol is proposed [16], where only the closest successful MSs to unsuccessful MSs are chosen as MRs. Compared to [8], the power consumption can be improved a lot at the cost of providing the channel state information (CSI) of all MSs. Another energy efficient cooperative multicast scheme is proposed in [17], which selects relays based on the conditions of nearby users. Assuming

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100% user coverage, this scheme can achieve almost the same throughput performance with less energy consumption as the conventional one-stage multicast transmission. Although previous researches start to investigate power efficient schemes, it remains unknown how to design two-stage multicast transmission with optimized power consumption. For instance, in [8], the transmission power of the BS at the 1st stage PBS,C is simply set to a fixed value, which will ensure half of MSs in the cell receive the data from BS. Moreover, the conventional scheme ensuring 100% user coverage is not practical due to its poor saturated system throughput when the number of MSs is large. Therefore, instead of improving system throughout with 100% coverage, this paper investigates two-stage cooperative multicast transmission aiming to guarantee a practical coverage ratio (such as 95%) with minimum power consumption. Note that an exact analysis of the optimization of transmission power is difficult, which depends on various parameters and system configurations, such as the BS transmission power at the 1st stage PBS,C , user density, the number and positions of MRs, receive signal processing algorithms, and so on. As illustrated before, the BS consumes most energy in wireless networks. Hence, the BS power should be one of the most important parameters when designing a power efficient system. This paper focuses on the relationship between PBS,C and the total power consumption of the two-stage cooperative multicast transmission. To facilitate theoretical analysis, it is assumed that at the 2nd stage, a selective combining algorithm based on average received signal strength (SCA) is adopted at the receiver where MSs only receive the signal from the nearest MR. Moreover, the user density is supposed to be sufficiently high. A MR arrangement scheme based on sector ring structures is firstly proposed for the 2nd stage transmission, aiming to provide uniform coverage performance throughout the cell. Then, constrained by the guaranteed coverage, an analysis is carried out on the relationship between PBS,C and the total power consumption. Since a lot of numerical computation is needed to obtain the optimal PBS,C with the proposed scheme, further approximations are exploited to provide a simple theoretical estimation for the optimal PBS,C , whose effectiveness is verified by numerical results. It is shown that compared to the conventional one-stage multicast transmission, the proposed two-stage cooperative scheme can reduce the total power consumption and the BS power consumption by more than 40% and 80%, respectively, thanks to the cooperation provided by MSs. Although the proposed method is derived by using SCA scheme, it is demonstrated through simulation that using a practical CP combining scheme, when the user density is higher than 2·10−4, a coverage ratio of 95% can be guaranteed with the optimal BS transmission power and MR arrangement from the proposed scheme. Moreover, the effectiveness of the proposed MR arrangement is verified by simulations where it outperforms other three arrangements. It is also shown that targeting at minimizing the total transmission power with guaranteed coverage, the proposed scheme significantly outperforms the existing two-stage scheme in terms of energy consumption and efficiency. The rest of the paper is organized as follows. Section II describes the system model and the basic principles of

conventional one-stage multicast and two-stage cooperative multicast schemes with guaranteed coverage. In Section III, given reasonable assumptions, a MR arrangement scheme is firstly proposed, followed by an analysis on the relationship between the BS transmission power at the 1st stage and the total power consumption of the two-stage cooperative multicast transmission. Pseudo codes and practical implementation of the proposed scheme are also described in this section, together with a simplified theoretical estimation method for the optimal BS transmission power. To verify the effectiveness of the proposed two-stage cooperative multicast scheme, numerical and simulation results are presented in Section IV. Finally, conclusions are drawn in Section V. II. S YSTEM D ESCRIPTION Consider the broadband downlink transmission in cellular systems based on OFDM. Assuming a single antenna transceiver and a slow fading channel, the received signal at MS k is given by rk (t) =

M−1 PBS αBS,k hk (t) dm ej2πmΔf t + ηk (t)

(1)

m=0 −γ where PBS is the BS transmission power, α2BS,k = A1 ·DBS,k stands for the path loss from BS to MS k, where A1 is a constant, DBS,k is the distance between BS and MS k and γ L−1 is the path loss parameter. hk (t) = l=0 hk,l δ(t − τk,l ) is the microscopic L−1multipath 2Rayleigh fading with a normalized power of l=0 E{|hk,l | } = 1. Note that shadowing is not considered in the channel model since it plays a less important role compared to the path loss and microscopic fading [18]. dm is the multicast data transmitted on the mth sub-carrier with a unit power, Δf is the sub-carrier spacing, t ∈ [0, Tg + Ts ], where Tg and Ts are the time duration of cyclic prefix (CP) and effective OFDM symbol, respectively, and ηk (t) represents the zero mean Gaussian noise with a 2 variance of σnoi . Assume that the length of CP is longer than the maximum delay of the multipath channel. After ideal synchronization and FFT, the received signal on the mth subcarrier of MS k is given by

Ym,k

=

L−1 PBS αBS,k ( hk,l e−j2πmΔf τk,l )dm + zm,k

=

l=0 PBS αBS,k Hm,k dm + zm,k

(2)

where Hm,k follows Rayleigh fading with an average power of 1 and zm,k is the zero mean background noise with a variance 2 of σnoi . Thus, the signal to noise ratio (SNR) of Ym,k is 2 given by SN Rm,k = PBS α2BS,k |Hm,k |2 /σnoi . Assume that a block of continuous sub-carriers are allocated for multicast transmission and they experience similar channel fading [1920]. Therefore, in the following context, the received signal on one sub-carrier is concerned. A. One-stage Multicast Transmission Focusing on the total system power consumption, analysis is carried out for conventional one-stage multicast transmission on how to get the power given a desired transmission data rate

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. ZHOU et al.: TWO-STAGE COOPERATIVE MULTICAST TRANSMISSION WITH OPTIMIZED POWER CONSUMPTION AND GUARANTEED COVERAGE

Time Interval 1st Stage T

1

BS

T

2nd Stage T 2

BS

MR1(B1) UMS1(B2) BS transmits data at the 1st stage SMS: MS that successfully receive the data at the 1st stage

Fig. 1.

SMSs chosen as MRs transmit data at the 2nd stage UMS: MS that need cooperative transmission at the 2nd stage

System model for two-stage cooperative multicast transmission

Rone , a cell radius R and a coverage ratio Cth [21]. According to Shannon theory, the required SNR SN Rone can be obtained from Rone = B · log2 (1 + SN Rone ), where B is the system bandwidth. To successfully receive the multicast data, the SNR of received signal SN Rk (obtained from SN Rm,k by omitting m) must be no less than SN Rone . Instead of making all MSs successfully receive the data, the transmission power of the BS, PBS , is set to a value that can ensure a coverage of Cth for the service, e.g., 95% of all MSs in the cell can successfully receive the multicast signal. Assuming that each BS covers a circular area of radius R and all MSs are uniformly distributed, whose probability density function (pdf) depends on its distance z from the BS, given by 2z , z ∈ (0, R] (3) R2 Given the SNR of MS k as SN Rk = PBS · 2 α2BS,k |Hk |2 /σnoi and the multipath fading component Hk as a Rayleigh distribution with an average power of 1, the coverage ratio in the cell of radius R with a BS power of PBS is given by [22] R Cth = P (SN Rk ≥ SN Rone ) · fd (z)dz (4) fd (z) =

0

=

2(A1 · PBS )2/γ 4/γ

2 2 Rγ SN Rone σnoi −2/γ SN Rone Γ( , ) γ A1 · PBS

γR2 σnoi q where Γ(p, q) = 0 tp−1 exp(−t)dt is the incomplete gamma function. Therefore, for a multicast service of rate Rone , to ensure a coverage of Cth within a cell of radius R, the transmission power PBS is decided by (4). B. Two-stage Cooperative Multicast Transmission This paper focuses on two-stage cooperative multicast transmission schemes, aiming to provide the same coverage performance as that of one-stage transmission with minimized power consumption. In two-stage cooperative multicast transmissions, the total transmission time interval T is divided into

3

two parts, T1 and T2 . As shown in Fig. 1, at the 1st stage with a time duration of T1 , the BS transmits multicast data at a rate of Rtwo,1 with a power of PBS,C such that only a part of all MSs can successfully receive the data. Denote these MSs as successful MSs (SMS: indicated by gray circles in Fig. 1) and the MSs that fail to receive data at the 1st stage as unsuccessful MSs (UMS: indicated by white circles). It can be expected that in areas that are farther away from the BS, there are more UMSs. So it is reasonable to choose SMSs having a larger distance to the BS as MRs (indicated by black circles) [23]. For example, the SMSs with a distance larger than 0.7R can be selected, while no SMSs will be taken from areas within 0.7R where the target coverage ratio is expected to be achieved at the 1st stage and no more MRs are needed at the 2nd stage. Then, at the 2nd stage with a time duration of T2 , the selected SMSs are employed to further convey the multicast data at a rate of Rtwo,2 to the UMSs. For example, MR1 successfully transmits data to UMS1 at the 2nd stage. Obviously, compared to the power needed by the BS to convey the data to UMS1 , the transmission power of MR1 is much less due to the shorter distance. Therefore, it can be expected that to provide the same performance with same conditions, two-stage cooperative multicast transmission should be more power efficient than the conventional one-stage transmission due to the path loss gain provided by shorter communication distances. Given the same multicast service as that in conventional transmission, the data transmitted in the time duration of T , T1 and T2 should be the same. Thus, it can be obtained that Rtwo,1 T1 = Rtwo,2 T2 = Rone T . Meanwhile, assume that the transmission data rate can be chosen according to the channel capacity, the relationship between the data rate and the received SNR can be obtained as Rone = Blog2 (1 + SN Rone ), Rtwo,1 = Blog2 (1 + SN Rtwo,1 ) and Rtwo,2 = Blog2 (1 + SN Rtwo,2 ). Hence, T1 · Blog2 (1 + SN Rtwo,1 ) = T · Blog2 (1 + SN Rone) and T2 · Blog2 (1 + SN Rtwo,2 ) = T · Blog2 (1 + SN Rone ). The corresponding SNR thresholds at the 1st and 2nd stage are then given by SN Rtwo,1 = (1 + SN Rone )T /T1 − 1 and SN Rtwo,2 = (1 + SN Rone )T /T2 − 1, respectively. In this paper, it is assumed that T1 = T2 and SN Rtwo,1 = SN Rtwo,2 = SN Rtwo . At the 2nd stage, more than one SMSs can be employed to forward data to UMSs. In real systems, when the CP is sufficiently long, signals from all MRs could fall within a CP duration and a stronger signal may be constructed (CP combining: CPC). Although CPC is practical, it would be difficult to decide the coverage area of a MR with CPC since any location is covered by multiple MRs. Therefore, to facilitate the performance analysis, a SCA scheme is adopted where UMS only receives the signal from the nearest MR, while the signals from other MRs are ignored. As shown in Fig. 1, consider a MR at point B1 with a transmission power of PMS . For a UMS located at point B2 the received signal from the MR is given by YB2 = PMS αB1 ,B2 HB1 ,B2 d + zB2 (5) −γ stands for the path loss from where α2B1 ,B2 = A2 · DB 1 ,B2 the MR to the UMS, A2 is a constant which is different from A1 , since the path loss model for the MR to UMS can be



different from that for BS to MS, and DB1 ,B2 is the distance between the MR and UMS. Therefore, the SNR of YB2 is 2 given by SN RB2 = PMS · α2B1 ,B2 |HB1 ,B2 |2 /σnoi . For a region centered at point B1 with a radius of RMS , the coverage ratio of the MR is given by RM S CMS = P (SN RB2 ≥ SN Rtwo ) · fd (z)dz (6) 0

=

2(A2 · PMS )2/γ 4/γ

2 σ γRMS noi

Success probability Average: Cth

2 2 Rγ SN Rtwo σnoi −2/γ SN Rtwo Γ( , MS ) γ A2 · PMS

(0,0)

III. P OWER C ONSUMPTION A NALYSIS A. Basic Assumptions

RMS 0

It can be seen from Fig. 1 and previous researches that the performance of two-stage multicast transmission depends on a number of parameters such as the BS transmission power at the 1st stage PBS,C , the number of MRs, the user density, the schemes to locate MRs, the receive signal processing schemes, and so on. Therefore, an exact analysis for the power consumption is difficult. On the other hand, as explained in the introduction, more than 70% energy in wireless networks could be consumed by BSs. So the transmission power of BSs is one of the most important parameters when designing energy efficient systems. To focus on the relationship between PBS,C and the total power consumption Ptot of the two-stage multicast transmission, several basic assumptions are adopted as follows. Firstly, as stated before, a SCA scheme is employed for receiver signal processing, where the UMS only gets the signal from the nearest MR. Secondly, the user density is supposed to be sufficiently high. Given a fixed MS transmission power PMS , the total power consumption Ptot depends on the transmission power of BS at the 1st stage PBS,C and the number of MRs used for the 2nd stage transmission, which is highly related to the density of the MSs in the cell. When the density is low, for example, there is only one MS, the conventional one-stage transmission must be employed and it is impossible to save power consumption via the two-stage scheme. On the other hand, assuming that the density is high enough, it can be ensured that any location in the cell can be covered by at least one MR at the 2nd stage.

RMS 1

B. Proposed MR Arrangement Scheme Aiming to provide uniform coverage performance for different locations of the macro cell, a MR arrangement based on sector ring structures is proposed for the 2nd stage transmission as follows. As shown in Fig. 2, given the desired coverage ratio Cth , for any BS transmission power PBS,C , a radius RBS,C can be obtained using (4), within which the coverage ratio is Cth . Hence, there is no need to further employ MRs in this area and MRs should be located in the annular region with radius from RBS,C to R. This annular region is further divided into several rings, where the coverage ratio at the 1st stage is below Cth and decreases as the distance from the BS increases. So each ring needs MRs to improve the overall coverage ratio to Cth after the two-stage transmission, and the required coverage ratio of the MRs increases with their distances from the BS. Note that MRs have a fixed

RMS 2

RBS,C (0,0)

Fig. 2.

r

(x,y)

R

MR arrangement based on sector ring structures at the 2nd stage

transmission power. So their coverage radius decreases as their distances from the BS increases and is denoted as RMS (0), RMS (1), and so on. The farther away the ring is from the BS, the more MRs should be employed. The following issues should be noted for the proposed MR arrangement scheme. First of all, after two-stage cooperative multicast transmission, to guarantee a coverage ratio of Cth for the macro cell, it is not necessary for the coverage ratio of each ring to be Cth . It can be lower than Cth if another ring provides a coverage ratio higher than Cth . However, from the fairness point of view, it is desirable that each ring of the macro cell could achieve the same coverage ratio of Cth . Secondly, although the transmission power of MR is fixed, the required coverage capability varies according to its position. When it is closer to the BS, the success probability of the 1st transmission is higher. Therefore, to achieve Cth after twostage transmission, the required success probability of the 2nd transmission can be lower. Accordingly, the required coverage ratio of the MR is lower and the corresponding coverage radius is larger. Thirdly, assume that the cellular coverage area of MR is equivalent to the sector ring that contains it. If there are totally M rings, denote the coverage radius of MR in the ith ring as RMS (i)(i = 0, · · · , M − 1), so the corresponding area is 2 given by SMS,i = πRMS (i). Moreover, the area of the ith i ring is SRing,i = π(RBS,C + 2 j=0 RMS (i))2 − π(RBS,C + i−1 2 j=0 RMS (i))2 . Therefore, to ensure the coverage ratio of the ith ring, the number of MRs needed can be approximated


by

5

be approximated by the coverage ratio of the sector ring SRing,i SMR,i

N (i) ≈

(7)

(RBS,C +2

i

2

RMS (i)) −(RBS,C +2

j=0

=

i−1

CBS (i) ≈

RBS,C +2

2

RMS (i))

j=0 2 (i) RMS

=

Then, the total power consumption is given by Ptot = PBS,C

M−1 T1 T2 + N (i)PMS T T i=0

(8)

which is decided by PBS,C and N (i). Therefore, to carry out power consumption analysis, the relationship between PBS,C and N (i) (or RMS (i), equivalently) should be investigated firstly. C. Coverage Radius of MR at the ith ring Consider any position (x,y) in the ith ring. The success probabilities of the 1st and 2nd stage transmissions are given by stwo,1 (x, y) and stwo,2 (x, y), respectively, i.e., the MS at (x,y) can receive the multicast data from the BS at the 1st stage with a probability of stwo,1 (x, y) or from the MR at the 2nd stage with a probability of stwo,2 (x, y). Then after the two-stage transmission, the final success probability becomes stwo (x, y) = 1 − (1 − stwo,1(x, y)) · (1 − stwo,2 (x, y)), and the coverage ratio of Cth can be guaranteed if stwo (x, y) satisfies the following equation

1

Cth =

2 (i) πRMS

RBS,C +2

RBS,C +2

R2MS − x−(RBS,C +2

− R2MS− x−(RBS,C +2

t=x− RBS,C +2

i−1

j=0

i−1 j=0

i−1 j=0

i j=0

i−1 j=0

RM S (j)

(9)

RM S (j)

RMS (j)+RMS (i))

RMS (j)+RMS (i))

RMS (j)+RMS (i)

2

2 stwo (x,y)dxdy

+

1

2 (i) πRMS

−

1

CBS (i)

RMS (i) −RMS (i)

RMS (i)

√R2MS (i)−t2 −

√

stwo,2 (x,y)dtdy √ 2 RMS (i)−t2

CM S (i)

R2MS (i)−t2

stwo,1(x,y)stwo,2(x,y)dtdy √ 2 (i) πRMS −RMS (i) − R2MS (i)−t2

where CBS (i) and CMS (i) are the coverage ratios of the cellular area of radius RMS (i) after the 1st and 2nd transmissions, respectively. To obtain the relationship between PBS,C and RMS (i), (9) is approximated by Cth ≈ CBS (i) + CMS (i) − CBS (i)CMS (i)

−

(10)

Note that the cellular coverage area of MR is assumed to be equivalent to the sector ring that contains it. Then CBS (i) can

i j=0

i−1 j=0

RM S (j)

RM S (j)

P (SN Rk≥ SN Rtwo )·fd (z)dz

i−1 (RBS,C +2 RM S (j))γ j=0 2 2/γ Γ( , ) 2 2(A1 · PBS,C ) γ A1 ·PBS,C /(SN Rtwo σnoi ) 2 )2/γ i−1 γ(SN Rtwo σnoi (RBS,C + 2 RMS (j))2 j=0 i (RBS,C +2 RM S (j))γ j=0 2 Γ( γ , A1 ·PBS,C /(SN Rtwo σ2 ) ) noi

(RBS,C + 2

i

(11)

RMS (j))2

j=0

i which is decided by PBS,C and j=0 RMS (j). Moreover, CMS (i) can be obtained from (6) which depends on i RMS (i). Consider the 0th ring where R j=0 MS (j) = RMS (0). Using (6), (11) and (10), the relationship between PBS,C and RMS (0) can be obtained, which can be denoted as RMS (0, PBS,C ). Then for the 1st ring, the relationship between PBS,C and RMS (1) can be expressed as RMS 1, PBS,C , RMS (0) = RMS (1, PBS,C ). Similarly, RMS (i) is related to PBS,C by RMS (i, PBS,C ). Then, using (7), N (i) can be expressed as N (i, PBS,C ). Hence the total power consumption can be minimized by Ptot

M−1 T1 T2 + = min {PBS,C N (j, PBS,C )PMS } (12) PBS,C T T j=0

where the total number of rings M is decided by increasing the number of rings until the coverage area of the BS and all the rings is no less than the macro cell coverage area, which can be given by M = min{R ≤ RBS,C + 2 i

−−−−−−−−−−−−−−−−−−−√ −−−−−→ RMS (i) R2M S (i)−t2 1 stwo,1 (x, y)dtdy = √ 2 (i) πRMS −RMS (i) − R2M S (i)−t2

RBS,C +2

i

RMS (j)}

(13)

j=0

Note that for a given cell radius ofR, it is possible that M−2 the chosen M results in RBS,C + 2 j=0 RMS (i) < R < M−1 RBS,C +2 j=0 RMS (i). That means, the macro cell cannot be covered by integer number of rings. In this case, to ensure a coverage ratio of Cth for the cell, part of the transmission power of MRs is wasted. To be energy efficient, the corresponding PBS,C should be reduced or increased to ensure that the cell can be covered by integer number of rings. So it can be expected that to minimize the total transmission power, the optimal PBS,C should make the macro cell be exactly covered by the BS and integer number of rings. D. Practical Implementation According to the proposed two-stage cooperative multicast transmission scheme, numerical computations are needed to get the optimal PBS,C that achieves the minimum total power consumption. The algorithm is described as follows. Step 1: Set system parameters like PMS , R, Cth , SN Rone , T , T1 , and T2 and calculate SN Rtwo . Step 2: Search for the optimal PBS,C from a high value (e.g., the transmission power of BS in one-stage transmission



PBS ) with a search step Δp . Set n = 0 as the index for the value of PBS,C and PBS,C (n) = PBS . Step 2.1: According to (4), RBS,C can be calculated with the given values of PBS,C (n), Cth and SN Rtwo . Set i = 0 as the index for the ring next to the coverage area of the BS. Step 2.2: For the MR in the ith ring, calculate the required coverage ratio CBS (i) using (11). Step 2.3: Similar to Step 2.1, calculate RMS (i) with the given values of PMS , CBS (i) and SN Rtwo using (4). Then the number of MRs needed in this ring N (i, PBS,C ) can be obtained using (7). Step 2.4: If RBS,C + 2 ij=0 RMS (j) < R, the macro cell cannot be covered by the BS and (i + 1) rings. Set i = i + 1 i and go to Step 2.2. If RBS,C + 2 j=0 RMS (j) ≥ R, the whole cell has been covered and there is no need for more rings. Step 2.5: Calculate the total transmission power Ptot (n) corresponding to PBS,C (n) using (12). Set PBS,C (n + 1) = PBS,C (n)−Δp . If PBS,C (n+1) is still larger than a predefined lower bound, set n = n + 1 and go to Step 2.1. Step 3: Find the minimum total transmission power from the set of values {ptot (n)} and the corresponding PBS,C is ∗ the desired optimal BS transmission power PBS,C . ∗ Although the numerical search for PBS,C needs a lot of computation, it is done offline and will not increase the complexity of the system. In practice, the proposed twostage cooperative multicast transmission with optimized power consumption and the MR arrangement based on sector ring structures could be carried out as follows. At the 1st stage, ∗ the BS transmits multicast data using a power of PBS,C . Since the number of rings, the number of MRs in each ring and their ∗ coverage radiuses are all calculated when searching for PBS,C , a map of MR locations suggested by the proposed scheme can be obtained and stored in the BS. After the 1st stage transmission, each SMS should send a message to the BS, indicating that it has successfully received the data. Location information of each SMS is needed at the BS, which might be obtained using terminal-based or network based positioning techniques [24]. Then the BS should select the SMS closest to a suggested MR location as the MR and send messages to notify these SMSs. At the 2nd stage, the chosen SMSs acts as MRs and transfer multicast data to UMSs. It can be seen that compared to conventional one-stage multicast transmissions, the proposed two-stage cooperative scheme need two simple signalings after the 1st stage transmission to determine which SMSs should be MRs. Moreover, additional location information is needed, which should not be a difficult task with the development of location based services. E. Theoretical Estimation It can be seen that a lot of computation is needed in the previous numerical search for the optimal BS transmission power achieving the minimum total power consumption. In this section, further approximations are adopted to provide a simple theoretical estimation for the optimal BS transmission power. For the success probability after two-stage transmission at point (x,y), stwo (x, y) is set to Cth so that the coverage ratio can be guaranteed. Denoting the distance between (x,y)

TABLE I S YSTEM PARAMETERS Carrier Frequency Frequency Band B Path Loss from BS to UE P LBS (dB) Path Loss from UE to UE P LM S (dB) Path Loss parameter γ Transmission power of BS for conventional one-stage multicast PBS Transmission Power of MS PM S Noise Power Spectrum N0 Coverage Ratio Cth Cell Radius R Rate of multicast Rone

2.5G 10M 17.39 + 37.6log10 (d[m]) 37.78 + 37.6log10 (d[m]) 3.76 33.88W (45.3dBm) 0.20W (23dBm) -169dBm/Hz 95% 1500m 0.89bps/Hz

and the BS as r (see Fig. 2), it is obtained that stwo (r) = 1 − 1 − stwo,1 (r) · 1 − stwo,2 (r) = Cth . Note that stwo,1 (r) = exp(−

2 SN Rtwo · σnoi ) A1 · PBS,C · r−γ

(14)

Then stwo,2 (r) should satisfy stwo,2 (r)

1 − Cth 1 − stwo,1 (r) 2 SN Rtwo · σnoi = exp(− −γ ) A2 · PMS · RMS

= 1−

(15)

It can be obtained that 1/γ A2 PMS 1 − stwo,1 (r) )· 2 RMS (r) = ln( (16) Cth − stwo,1 (r) σnoi · SN Rtwo which is further averaged over RBS,C to R to get a coverage radius RMS independent of r. Then, the number of MRs needed at the 2nd stage transmission is estimated by Ntot =

2 π(R2 − RBS,C )

πRMS

2

(17)

As shown in Fig. 2, the ring from RBS,C to R cannot be seamlessly covered by the MRs with a cellular coverage area. So Ntot obtained from (17) is a lower bound for the actual number of MRs needed to improve the coverage ratio to Cth . Thus, the total transmission power can be optimized as follows Ptot = min {PBS,C PBS,C

2 R2 − RBS,C T1 T2 + · PMS } 2 T T RMS

(18)

Since both RBS,C and RMS are functions of PBS,C , Ptot is only decided by PBS,C and the optimal PBS,C that achieves the minimum total transmission power can be found by numerical methods. IV. P ERFORMANCE I NVESTIGATION A. Numerical Results The system parameters are shown in Table I. Referring to practical network settings, the target coverage ratio Cth is chosen to be 95%, the transmission power of BS for conventional one-stage multicast is 33.88W (45.3dBm) and the transmission power of MS is 0.20W (23dBm). The radius of the macro cell is set to 1500m. Moreover, two different path loss models are employed for the BS to MS and the MR to


7

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MS transmission [25]. It should be noted that the value of path loss depends on a number of elements including the height of transmitter, the height of receiver, the reference distances, the carrier frequency, and the distance between the transmitter and receiver. Since the BS and MR have different heights and reference distances, the path loss models for the BS to MS and for the MR to MS should be different. Using these settings, according to the proposed scheme (12), the optimal BS transmission power achieving the minimum total power consumption is shown in Fig. 3, which is obtained by searching PBS,C from 4W to 64W. Moreover, the corresponding number of MRs needed to guarantee a coverage ratio of 95% is illustrated in Fig. 4. It can be seen that in general, the total power consumption decreases as PBS,C increases from 4W and reaches the minimum value of 19.2W when PBS,C = 11.32W . Corresponding to the optimal PBS,C , the macro cell is exactly covered by the BS and three rings, where 31, 47 and 60 MRs are allocated with coverage radiuses of RMS (0) = 127.9, RMS (1) = 104.9 and RMS (2) = 94.0 meters, respectively. So the total number of MRs is 138, as shown in Fig. 4. When PBS,C increases further, the total power consumption becomes higher. Note that the total power consumption of the proposed scheme changes in a staggered way with PBS,C . This is because the number of MRs needed to provide the desired coverage ratio does not change smoothly. For example, when PBS,C = 6W , according to the proposed scheme, the whole cell can be exactly covered by the BS and four rings with 190 MRs. As PBS,C increases, its coverage area becomes larger and the sector ring from PBS,C to R gets smaller. But the system still needs four rings to cover the whole cell with a guaranteed coverage ratio of 95%, even some power of MRs is wasted because the actual

9

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19

24

29

34 39 44 49 545964

(W)

Fig. 4. Required number of MRs for guaranteed coverage as a function of BS transmission power

coverage area is larger than the macro cell. The number of MRs even slightly increases due to the reduced width of rings. When PBS,C is further increased to 11.32W, the cell can be exactly covered by the BS and three rings with 138 MRs. Thus, the number of MRs and the total transmission power reduce sharply. It can be seen that to be energy efficient, the optimal PBS,C must be obtained when the macro cell can be exactly covered by the BS and integer number of rings. This consists with the analysis of (13) in Sec. III. Moreover, the optimal BS transmission power and the number of MRs obtained from the simple theoretical estimation (18) are also plotted in Fig. 3 and Fig. 4, respectively. It can be seen that the estimation for the optimal BS power is close to the numerical results of the proposed scheme, which verifies the effectiveness of the theoretical estimation (18). For comparison, the total transmission power of conventional one-stage multicast (33.88W) is also shown in Fig. 3. Using the proposed two-stage cooperative multicast transmission with a guaranteed coverage ratio of 95%, the total power consumption can be saved by more than 40%. This is because the proposed two-stage cooperative transmission can benefit from path loss gain. Compared to the long communication distance between the BS and MS, the distance between the MR and UMS is much shorter. Although for the same distance, the path loss between MR and UMS is larger than that between BS and MS, as shown by the two different path loss models [25], the resultant path loss gain is considerable as a whole. Moreover, the BS power consumption can be saved by more than 80%, thanks to the cooperation provided by MSs. This would be attractive to operators. If customers are properly stimulated and willing to provide cooperation, the power consumption of the BS can be greatly reduced.



1

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40 0.95

Scheme-k-Random (two-stage) Scheme-0-Prob (two-stage) Scheme-BS-Prob (two-stage) Proposed scheme (two-stage) Conventional one-stage

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0.9

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Fig. 5. Coverage performance of the proposed scheme with different signal combining schemes

B. Simulation Results Next, simulations are carried out to verify the numerical results and investigate the performance of the proposed two-stage cooperative multicast scheme with optimized BS transmission power and the MR arrangement based on sector ring structures. First of all, the coverage performance is shown in Fig. 5 as a function of user density when different signal combining schemes are considered. Note that the CP combining (CPC) collects all useful signals that fall into the CP duration, selective combining based on instant signal strength (SCI) chooses the strongest signal, and SCA picks the signal from the nearest MR which is the scheme used in analysis. It can be seen that the coverage ratio increases with the density. When the density is low, the coverage ratio of 95% cannot be achieved. This is because when the density is low, there are not enough SMSs to be selected as MRs and the coverage performance is degraded. It is reasonable since the proposed scheme is obtained by assuming high density. Using SCA, the coverage ratio approaches 95% at high density, while using CPC and SCI, the coverage ratio exceeds 95% when the density is larger than 2 · 10−4 . Due to the fading effect, the signal from the nearest MR selected by SCA may not be the strongest one selected by SCI, while CPC can collect multiple useful signals including the nearest and the strongest ones. Thus, CPC and SCI could provide stronger received signals and thus performs better than SCA. Since the coverage ratios of CPC and SCI are higher than 95% when the density is high, it can be expected that more power saving is possible with CPC and SCI if the coverage ratio is kept at 95%. So the energy performance of the proposed scheme based on SCA provides an upper bound for the minimum energy consumption that can be achieved in practice. In conclusion, when the

10 -5 10

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density(O)

Fig. 6. Total power consumption of two-stage transmission with different MR arrangement

user density is higher than 2 · 10−4 , using practical signal combining schemes such as CPC, the proposed two-stage cooperative scheme with optimized BS transmission power and the MR arrangement based on sector ring structures can provide desired multicast services with guaranteed coverage. As shown in analytical results, for the proposed twostage cooperative multicast transmission, the transmission power at the 2nd stage (decided by the MR arrangement) is more than twice of that at the 1st stage and dominates the energy consumption performance. It can be expected that the MR arrangement plays an important role in the energy consumption performance [23,26]. To verify the effectiveness of the proposed MR arrangement scheme based on sector ring structures, three other schemes are designed for comparisons. In the 1st scheme, for each BS transmission power, find the coverage radius RBS,C within which the coverage ratio is Cth = 95%. Then MRs are randomly located in the annular region from k · RBS,C to R, where k is a parameter that could be optimized via simulations. In this paper, k is set to 0.7 to provide good energy consumption performance with various densities. This scheme is denoted as Scheme-k-Random. In the 2nd scheme, the MRs are located in the annular region from 0 to R, but with a probability that is proportional to the failure probability at the 1st stage. That means, for locations with higher failure probability such as the cell edge, more MRs are needed, while for locations with lower failure probability such as places nearer to the BS, less MRs should be positioned. This scheme is denoted as Scheme-0-Prob. The 3rd scheme is similar to Scheme-0-Prob with MRs located in the annular region from RBS,C to R. So it is denoted as Scheme-BS-Prob. As a function of user density, Fig. 6 illustrates the minimum total power consumption of different MR arrangement schemes when CPC is employed. For the three comparison


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Fig. 7. Total power consumption and throughput of the proposed scheme and Scheme [8]

schemes, to guarantee a coverage ratio of 95% at low user densities, the total power consumption is high, especially for Scheme-BS-Prob, which put the MRs outside of RBS,C . Then, as the density increases, the power consumption reduces rapidly. When λ is higher than 10−4 , the total transmission power becomes stable at around 24W, and there is no much difference between the three schemes. The power consumptions of the conventional one-stage and the proposed two-stage multicast transmission are also shown in Fig. 6. At high user densities, the three comparison two-stage cooperative transmission schemes all significantly outperforms the one-stage transmission, providing a power saving of around 30%, while the proposed scheme using the MR arrangement based on sector ring structures can further reduce the power consumption of the three comparison schemes by 20%. This demonstrates the superiority in power saving at high user densities of twostage schemes over the conventional one-stage scheme and the proposed MR arrangement scheme over the three comparison schemes. On the other hand, for low user densities, although the proposed scheme consumes less power with less users since there are not enough MRs, it cannot ensure a coverage ratio of 95% (See Fig. 5). Meanwhile, the three comparison two-stage schemes may consume more power than the onestage scheme in order to guarantee the coverage ratio. In summary, at high densities, the proposed MR arrangement provides the best power consumption performance among all investigated arrangements, while at low densities, the two-stage schemes may be inferior to the one-stage scheme and further investigations are needed to obtain the best MR arrangement for two-stage cooperative transmissions. Finally, as presented in introduction, several works have been published on two-stage cooperative multicast transmission in literature [8-9]. Although these schemes are designed for different targets, it would be interesting to compare the energy efficiency between the proposed scheme and existing

-2

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Fig. 8. Comparison of energy efficiency between the proposed scheme and Scheme [8] TABLE II M AIN DIFFERENCES BETWEEN S CHEME [8] AND THE PROPOSED SCHEME

Target Coverage ratio Additional signaling Additional information the 1st stage

the 2nd stage

BS transmission power Coverage ratio How to choose MR

Scheme [8] Maximize system throughput 100% 0 0 Fixed (19.95W (43dBm)) Fixed (50%) All SMSs

Proposed Scheme Minimize the total transmission power 95% 2 Location information of SMSs needed Optimized to achieve the minimum total transmission power Optimized with the BS power Selected SMSs closest to the MR position suggested by the proposed scheme

schemes such as the one in [8] (denoted as Scheme [8]). Table II lists the differences between the proposed scheme and Scheme [8]. Fig. 7 demonstrates the total power consumption and the system throughput as a function of user density. It can be seen that as the user density increases, the power consumption of Scheme [8] increases rapidly since it employs all SMSs as MRs. For the proposed scheme, the power consumption keeps stable for different user densities. On the other hand, although Scheme [8] is designed to maximize the system throughput, the proposed scheme provides higher throughput than Scheme [8]. This is because Scheme [8] ensures 100% coverage while the proposed scheme aims to provide a coverage ratio of 95%. So the system throughput of Scheme [8] is limited by the worst channel experienced by all MSs. Furthermore, energy efficiency is introduced as a performance criterion, which is defined as throughput per watt and shown in Fig. 8 for the two schemes. It can be seen that the proposed scheme has two orders higher energy efficiency than Scheme [8], and the performance gap increases with user density. This is because according to the proposed scheme, as



long as the cell radius and the MS transmission power are given, the number of MRs and their locations are determined and will not change with user densities. When more users are considered, the system throughput increases with the same power consumption. Therefore, the energy efficiency becomes higher and higher as the number of users increases. As a whole, targeting at minimizing power consumption with guaranteed coverage at high density, the proposed scheme outperforms Scheme [8] concerning energy consumption and efficiency, at the cost of two additional signalings and the need for the location information of all SMSs. V. C ONCLUSIONS This paper investigated the two-stage cooperative multicast transmission schemes, aiming to minimize the total transmission power while guaranteeing a practical coverage ratio. To analyze the relationship between the BS power at the 1st stage PBS,C and the total power consumption, it was assumed that a SCA combining scheme was adopted at the receiver and the user density was sufficiently high. After a MR arrangement was proposed based on sector ring structures, the total transmission power was analytically derived as a function of the BS transmission power PBS,C and the optimal PBS,C could be obtained through numerical search. Moreover, to reduce the complexity of the search, further approximations were employed to provide a theoretical estimation for the optimal PBS,C . The power consumption performance of the proposed two-stage cooperative multicast was extensively investigated through numerical and simulation methods. The following conclusions are drawn: 1) Compared to the conventional one-stage multicast transmission, the proposed two-stage cooperative scheme can reduce the total power consumption and the BS power consumption by more than 40% and 80%, respectively, thanks to the cooperation provided by MSs. 2) The theoretical estimation is close to the results obtained from the proposed scheme. So it can provide an accurate estimation for the optimal BS transmission power with much lower complexity. 3) Although the proposed scheme is derived based on SCA, using a practical CP combining scheme, when the user density is higher than 2 · 10−4 , a coverage ratio of 95% can be guaranteed with the optimal BS transmission power and MR arrangement from the proposed scheme. 4) The proposed MR arrangement based on sector ring structures achieves much better power consumption performance than other investigated arrangements at high user density. 5) Aiming to minimize power consumption with guaranteed coverage at high density, the proposed scheme significantly outperforms Scheme [8] concerning energy consumption and efficiency, at the cost of two additional signalings and the need for the location information of all SMSs. ACKNOWLEDGMENT This work was funded by Beijing Natural Science Foundation Major Project 2010 (4110001), National Natural Science Foundation (61201231)), and KC Wong Fellowship (the Royal Society).

R EFERENCES [1] J. She, P. Ho, and L. Xie, ”IPTV over WiMax: key success factors, challenges, and solutions,” IEEE Commun. Mag., vol. 45, no. 8, pp. 87-93, Aug. 2007. [2] S. Kota, Y. Qian, E. Hossain, and R. Ganesh, ”Advances in mobile multimedia networking and QoS,” IEEE Commun. Mag., vol. 45, no. 8, pp. 52-53, Aug. 2007. [3] K. Kang and T. Kim, ”Improved error control for real-time video broadcasting over CDMA2000 networks,” IEEE Trans. Veh. Tech., vol. 58, no. 1, pp. 188-197, Jan. 2009. [4] Introduction of the Multimedia Broadcast Multicast Service (MBMS) in the Radio Access Network (RAN); Stage 2 (Release 7), Mar. 2008. 3GPP RAN, 3G TS 25.346 V7.7.0. [5] Feasibility Study on Improvement of the Multimedia Broadcast/Multicast Service (MBMS) in UTRAN (Rel. 7), Dec. 2006. 3GPP RAN, 3G TR 25.905 v7.7.0. [6] C. Suh and J. Mo, ”Resource allocation for multicast services in multicarrier wireless communications,” IEEE Trans. Wireless Commun., vol. 7, no. 1, pp. 27-31, Jan. 2008. [7] B. Niu, H. Jiang, and H. Zhao, ”A Cooperative Multicast Strategy in Wireless Networks,” IEEE Trans on Vehicular Tech, vol. 59, no. 6, pp. 3136-3143, Jul. 2010. [8] F. Hou, L. Cai, P.H. Ho, X. Shen and J. Zhang, ”A cooperative multicast scheduling scheme for multimedia services in IEEE 802.16 networks,” IEEE Trans. Wireless Commun., vol. 8, no. 3, pp. 1508-1519, Mar. 2009. [9] H. Zhao and W. Su, ”Cooperative wireless multicast: performance analysis and power/location optimization,” IEEE Trans. Wireless Commun., vol. 9, no. 6, pp. 2088-2100, Jun. 2010. [10] China Mobile Research Institute, C-RAN White Paper: Green Evolution of Wireless Access Network, China Mobile Research Institute, v1.0.0 ed., 2010. [11] C. Han, T. Harrold, S. Armour, I. Krikidis, S. Videv, P. M. Grant, H. Haas, J. S. Thompson, I. Ku, C.-X. Wang, T. A. Le, M. R. Nakhai, J. Zhang, and L. Hanzo, “Green radio: radio techniques to enable energy efficient wireless networks,” IEEE Commun. Mag., vol. 49, no. 6, pp. 46-54, June 2011. [12] X. Cheng, C.-X. Wang, H. Wang, X. Gao, X.-H. You, D. Yuan, B. Ai, Q. Huo, L. Song, and B. Jiao, “Cooperative MIMO channel modeling and multi-link spatial correlation properties,” IEEE J. Selected Areas in Commun., vol. 30, no. 2, pp. 388-396, Feb. 2012. [13] C.-X. Wang, X. Cheng, and D. I. Laurenson, “Vehicle-to-vehicle channel modeling and measurements: recent advances and future challenges”, IEEE Commun. Mag., vol. 47, no. 11, pp. 96-103, Nov. 2009. [14] C.-X. Wang, X. Hong, X. Ge, X. Cheng, G. Zhang, and J. S. Thompson, “Cooperative MIMO channel models: a survey,” IEEE Commun. Mag., vol. 48, no. 2, pp. 80-87, Feb. 2010. [15] X. Cheng, C.-X. Wang, D. I Laurenson, S. Salous, and A. V. Vasilakos, “An adaptive geometry-based stochastic model for non-isotropic MIMO mobile-to-mobile channels”, IEEE Trans. Wireless Commun., vol. 8, no. 9, pp. 4824-4835, Sept. 2009. [16] S. M. Elrabiei and M. H. Habaebi, ”Energy efficient cooperative multicasting for MBS WiMAX traffic,” IEEE ISWPC2010, pp. 600-605, 5-7 May 2010. [17] J. Lee, Y. M. Lim, K. Kim and S. G. Choi , ”Energy Efficient Cooperative Multicast Scheme Based on Selective Relay,” IEEE Commun. Lett., vol. 16, no. 3, pp. 386-388, Mar. 2012. [18] N. Guan, Y. Zhou, H. Liu and J.L. Shi, ”An Adaptive Multicast Transmission Scheme with Coverage Probability Guarantees,” accepted by J. System Simulation, CASS, Jan. 2012. [19] H. Zhu and J. Wang, “Chunk-Based Resource Allocation in OFDMA Systems - Part I - Chunk Allocation,” IEEE Trans. Commun., vol.57, no.9, pp. 2734 C 2744, Sept. 2009. [20] H. Zhu and J. Wang, “Chunk-based Resource Allocation in OFDMA Systems - Part II: Joint Chunk, Power and Bit Allocation,” IEEE Trans. Commun., vol. 60, no. 2, pp. 499-509, Feb. 2012. [21] A. Goldsmith, Wireless Communications, Cambridge University Press, 2005. [22] S. Y. Baek, Y.J. Hong and D.K. Sung, ”Adaptive Transmission Scheme for Mixed Multicast and Unicast Traffic in Cellular Systems,” IEEE Trans. Veh. Technol., vol. 58, no. 6, pp. 2899-2908, Jul. 2009. [23] N. Guan, Y. Zhou, H. Liu, L. Tian and J.L. Shi, ”An Energy Efficient Cooperative Multicast Transmission Scheme with Power Control,” IEEE GLOBECOM2011, pp.1-5, Dec. 2011. [24] I. A. Junglas and R. T. Watson, “Location Based Services”, Commun. ACM, vol. 51, issue 3, pp. 65-69, Mar. 2008.


[25] IEEE 802.16m-08/004r5, “IEEE 802.16m evaluation methodology document,” Jan. 2009. [26] Y. Li, Q. Yin, W. Xu, and H.M. Wang, ”On the Design of Relay Selection Strategies in Regenerative Cooperative Networks with Outdated CSI,” IEEE Trans. Wireless Commun., vol. 10, no. 9, pp. 3086-3097, Sep. 2011.

Yiqing Zhou (S’03-M’05-SM’10) received the B.S. degree in communication and information engineering and the M.S. degree in signal and information processing from the Southeast University, China, in 1997 and 2000, respectively. In February 2004, she received the Ph.D. degree in electrical and electronic engineering from the University of Hong Kong, Hong Kong. Now she is a professor in Wireless Communication Research Center, Institute of Computing Technology, Chinese Academy of Sciences. Dr. Zhou has published over 50 papers and book chapter in the areas of wireless mobile communications. She is a senior member of IEEE and the associate/guest editor for IEEE Trans. Vehicular Technology, IEEE JSAC (Special issue on “Broadband Wireless Communication for High Speed Vehicles” and “Virtual MIMO”), WCMC, ETT and JCST. She is also the TPC co-chair of ChinaCom2012, the tutorial co-chair of IEEE WCNC2013 and the workshop co-chair of GlobeCom2011. Dr. Zhou has served many international conferences as a TPC member, including IEEE ICC, GlobeCom, WCNC and VTC.

Hang Liu received the B.S. degree in Mathematics and Applied Mathematics from Northwestern Polytechnical University in 2010. He is currently a MPhil candidate in University of Chinese Academy of Sciences, Chinese Academy of Sciences. His research focuses on cooperative multicast, interference management and network information theory.

Zhengang Pan , principle staff of Green Communication Research Center (GCRC) of China Mobile Research Institute (CMRI), is now leading a team working on the key technologies of next generation (5G) wireless communication systems. Before join CMRI this spring, Dr. Pan has been working with HongKong ASTRI for more than 6 years where he has been involved in multiple technical fields, from wireless communication (WiFi, WiMax, LTE), to mobile digital TV (T-DMB, DVB-T/H, CMMB), to wireline broadband access (HomePlug, MoCA), in both system/algorithm design and terminal SoC chip implementation. Dr. Pan has also been working with NTT DoCoMo Beijing Communication Labs Co. Ltd, on the frontier research for 4G wireless communication standards, including 802.11n, 802.16d/e, HSPA and LTE. Dr. Pan received his Ph.D degree in year 2004, from Department of Electrical and Electronic Engineering, the University of HongKong. Dr. Pan is expertised in many technical fields including time/frequency/sampling synchronization technology for singlecarrier/multi-carrier(OFDM/A) based system, channel estimation, forward error correction coding, multiple antennas systems (MIMO) and space-time processing/coding, cross layer optimization and so on. Dr. Pan has published more than 40 papers in top journals and international conferences, and filed 38 patents with 15 granted so far.

11

Lin Tian (M’07) is an assistant researcher of Wireless Communication Technology Research Center, Institute of Computing Technology, Chinese Academy of Sciences. She received her B.S and M.S. degree from Beihang University, Beijing, China in 2002 and 2005 respectively. In Apr. 2012, she received the Ph.D. degree from Institute of Computing Technology, Chinese Academy of Sciences. Her research interests include wireless resource management and multimedia multicast scheme in next-generation mobile communication systems. She has published more than twenty research papers in IEEE journals and international conferences. She is also the inventor of more than ten Chinese patents and pending applications. She currently serves as the Publication Chair of the 7th International ICST Conference on Communications and Networking in China, and as reviewers for numerous referred journals and international conferences.

Jinglin Shi currently serves as the director of Wireless Communication Technology Research Center in Institute of Computing Technology, Chinese Academy of Science (ICT/CAS). He is also a visiting professor of Beijing University of Posts and Telecommunications, University of Sydney, University of Wollongong and Macquarie University. His research interests include wireless communications system architecture and management, wireless signal processing theory, and wireless communication baseband processor design. As a team leader, he led the development of TD-SCDMA, WiMAX, and LTE protocol stack systems successfully. He is currently responsible for several national projects in broadband wireless communication, including TDD-LTE baseband chip design and research on radio resource management techniques towards IMTA. Prof. Shi has published 2 books and over 100 papers in telecommunications journals and conference proceedings and has more than 30 patents granted. He has also served in the organizing and technical committees of numerous national and international conferences. He was the General Co-chair of ChinaCom2012, and the member of the Technical Program Committee (TPC) of IEEE WCNC, IEEE ICC, IEEE AusWireless 2006, 7th IEEE ISCIT’07, and ChinaCom 2007/2009.

Guanghua Yang received his Ph.D. degree from the Department of Electrical and Electronic Engineering in the University of Hong Kong in 2006. From 2006, he served as post-doctoral fellow, research associate, and project manager in the University of Hong Kong. His research interests are in the general areas of communications, networking and multimedia. He is a member of the IEEE, and the PMI.