Cross-tier Cooperative Transmission Strategy inMacro-pico Heterogeneous Network

Chen Zhang†, Xin Su∗, Jie Zeng∗, Zejiao Li†, Yujun Kuang†

†University of Electronic Science and Technology of China∗Tsinghua National Laboratory for Information Science and Technology

Research Institute of Information Technology, Tsinghua University, Beijing, Chinazengjie@tsinghua.edu.cn

ABSTRACTTo fully exploit the benefits of heterogeneous network (Het-Net), in which macro BSs (base stations) and small BSs co-exist, the intercell interference mitigation and radio resourcemanagement has attracted general attention. We proposea cross-tier cooperative transmission strategy with precod-ing at downlink OFDMA resource block level, supportedby macro BSs and small BSs ,to reduce the intercell inter-ference in HetNet. Simulation results demonstrate the pro-posed strategy provides significant system throughput gaincompared with non-cooperative scheme.

Categories and Subject DescriptorsC.2.1 [Network Architecture and Design]: Wire-less communication

General TermsAlgorithms, Performance, Design

KeywordsHeterogeneous Network, Cooperative Transmission, Re-source Blocks Allocation

1. INTRODUCTIONDriven by the higher capacity and better user ex-

perience in future wireless systems, HetNet is adoptedin 3GPP LTE-Advanced to realize a higher spectrumefficiency. HetNet is deployed with macro BSs andsmall BSs (such as pico BSs, femto BSs, relay nodes)which have different characteristics such as transmit-ting power, bandwidth, capacity, backhaul, etc. Themacro BSs ensure the basic coverage while the smallBSs provide supplement capacity in hotspots and cov-erage holes.Range expansion (RE) demonstrated in [1] fully ex-

ploits the benefits of HetNet. However, users in REareas suffer strong interference from the closest macroBSs. In [2], the enhanced intercell interference coordi-nation (eICIC) techniques were presented which onlyconsider coordination in time domain. The intracell co-operation in HetNet is proposed in [3], but they focus

on the resource blocks allocation among macro BSs andrelays. In this paper, we consider a cooperative trans-mission strategy enabling the cooperative transmissionof the multi-BSs at resource blocks level to reduce theinterference in RE areas.The remainder of the paper is organized as follows.

In Section 2, the system model is introduced and sumthroughput calculation method is given. And in Sec-tion 3, cooperative transmission strategy and resourceblocks allocation algorithm are described. In Section 4,the system performance of proposed algorithm is simu-lated and analyzed, and the paper is concluded in Sec-tion 5.

2. SYSTEM MODELWe consider the downlink communication of HetNet

with macro and pico BSs coexistence. Each cell is di-vided into three hexagonal sectors and each sector isequipped with one macro and Np pico BSs. There areNs sectors. Nu UEs are unevenly distributed in the cellarea and they can be classified into three types. TheUE that receives solely from the macro BS or pico BSis denoted as an M-UE or P-UE. The UE that receivescooperative transmissions is denoted as a C-UE. Thereare N resource blocks (RBs) in a 10ms frame.In order to improve the edge and average user through-

put, we apply cooperative precoding algorithm whichenables multi-C-UEs receive signal from the coopera-tive cluster (one macro BS and K-1 pico BSs) using thesame radio resource blocks.We first formulate a K ×Kchannel matrix H between the transmitting nodes andreceiving nodes:

H =

√PMhM,1

√PPhP1,1 ...

√PPhPK−1,1√

PMhM,2

√PPhP1,2 ...

√PPhPK−1,2

......√PMhM,K

√PPhP1,K ...

√PPhPK−1,K

(1)

The received signal at the C-UE is:

y = HWs+ n =rcM,1 0 ... 0

0 rcP2,2... 0

......0 0 ... rcPK ,K

s1s2...sK

+

n1

n2

...nK

(2)

where rcM,1 and rcPk,kare equivalent channel gain be-

tween transmitting nodes and receiving nodes respec-tively, which can be obtained by different precodingscheme [4]. The downlink received signal to interfer-ence noise ratio (SINR) experienced by M-UE, P-UEand C-UE can be evaluated as following:

SINRM−UEk,i,0,n =

PM |hnk,i,0|

2∑Nsi′=1,i′ ̸=i

PM |hnk,i′,0|2 +

∑Nsi′=1

∑NPj′=1

PP |hnk,i′,j′ |2 + σ2

SINRP−UEk,i,j,n =

PP |hnk,i,j |

2∑Nsi′=1

PM |hnk,i′,0|2 +

∑Nsi′=1

∑NPj′=1,j′ ̸=j

PP |hnk,i′,j′ |2 + σ2

SINRC−UEk,i,j,n =

|rcM,1(Pk,k)

|2∑Nsi′=1,i′ ̸=i

PM |hnk,i′,0|2 +

∑Nsi′=1

∑NPj′=1,j′ ̸=j

PP |hnk,i′,j′ |2 + σ2

(3)The throughput of M-UEk in sectori on the RBn can

be calculated as:

TM−UEk,i,0,n = f(SINRM−UE

k,i,0,n ) (4)

And f(x) is the mapping relationship of SINR andthroughput[5]. Similarly, TP−UE

k,i,j,n and TC−UEk,i,j,n can be

obtained.

3. COOPERATIVE TRANSMISSION STRAT-EGY IN HETNET

3.1 Cooperative FrameworkThe cooperative transmission strategy is carried out

within a cluster of cooperative BSs, as shown in Fig.1.In our cooperative transmission strategy, the precondi-tion of cooperation between two BSs is that they can oc-cupy the same RBs. According to the proposed cooper-ative transmission strategy, the total RBs of the systemare divided into cooperative RBs and non-cooperativeRBs.Assuming the RBs occupied by a cooperative clus-

ter divided into twelve RB groups (RBGs). There aretwelve UEs associated with their own service BSs ac-cording to the best RSRP scheme. The resource blocksallocation is showed in Fig.1. The green RBGs are de-noted as the cooperative resource blocks of macro and

Figure 1: An example of cooperative transmis-sion strategy

pico1 BS. The yellow ones are denoted as the coopera-tive resource blocks of macro and pico2 BS. The othersare non-cooperative resource blocks allocated in eachBS. For example, UE4 in cell range expansion area ofpico1 BS could utilize the RBG3−4 together with UE2

if the cooperation is achieved between macro and pico1BS, while the RBG3−4 in macro BS was only utilizedby UE2 previously.

3.2 Cooperative Users SelectionIn the network, each UE feedbacks the channel qual-

ity information (CQI) to BSs. Then BSs forward thisinformation to the central scheduler. The selection of C-UEs in proposed cooperative transmission strategy canbe divided into two steps. Firstly, central scheduler se-lects the users located in the cell range expansion areasas C-UE sets. These users are under serious interferencefrom nearby macro BSs. The decision rule of C-UE inrange expansion area is shown as following:

UC−UEi,j = {k ∈ URE

i,j |SINRREk,i,j < T} (5)

where UREi,j is the users dropped in the range expan-

sion areas of picoj in ith cluster and T is the SINRthreshold to choose the C-UE, which could be decidedby percentage of the poor spectral efficiency users inrange expansion and the power biasing of macro andpico BSs. Next, for each RB of a cooperative cluster,identify one C-UE from the M-UE set to participatein cooperative transmission. Applying equation(2) toobtain the equivalent channel gains of different C-UEscombination, then the expected throughput could beevaluated to find the optimal C-UEs combination in dif-ferent RBs.

3.3 Resource Blocks AllocationResource blocks allocation that implemented by cen-

tral scheduler for cooperative UEs and non-cooperativeUEs based on the receiving CQI in HetNet. Central

scheduler notices the corresponding BSs the RBs ar-rangement information, then the C-UEs simultaneouslyserved by cooperative BSs.We investigate a cooperative resource blocks alloca-

tion strategy where radio resource control is realized ina centralized manner. In order to estimate the systemperformance better, we introduce the combined perfor-mance measurement function (CPM) as an optimizedobjective function shown in following:

CPM = (1− γ)SEarvg + γSEedge (6)

γ is compromise coefficient, and 0 < γ < 1. SEarvg

and SEedge is average user throughput and edge userthroughput respectively, γ could be selected as 0.5 as atrade off of the average and edge user performance.

4. SIMULATION CONFIGURATION AND RE-SULTS

The simulation operates in a cellular network with a19-cell 3-sector three-ring hexagonal cell structure, fol-lowing the guidelines for Case 1 described in the 3GPPtechnical report [6]. In each cell, ten pico BSs are ran-domly deployed at the hotspot areas. Downlink simula-tions are carried out for a 10MHz system with 30 UEsper macro cell. And biasing of 9dB toward pico BSs forthe range expansion.Throughput performance of total four HetNet cases

are compared by means of system level simulation. Inthe first case, the users associate with BSs based on bestRSRP without range expansion. In the second case,range expansion is adopted without enhancement tech-nology, the users selected the best server BS under therule of 9dB biasing toward pico BSs. In the third case,typical eICIC is adopted to enhance range expansion.In the last case, the proposed cooperative transmissionstrategy is adopted. The user throughput comparisonin four cases is shown in Fig.2. The range expansionbrings obvious downgrade in sum system throughput,and the average user throughput decreases by 9.4%. Aconclusion could be drawn that the heavy macro trafficoffload comes at the cost of sum system throughput.In order to improve the system performance with

range expansion, we select the users which in the cellrange expansion areas as C-UEs. The final number ofC-UEs in our simulation is 402. In order to estimatethe performance of our cooperative scheme, we com-pare this with the system throughput under the exist-ing eICIC technology. The ratio of ABS (Almost BlankSubframe) and effective downlink subframe is set as 1

6in our simulation. In Fig.2, the average user through-put increases by 13.2% and 14.1% under eICIC technol-ogy and our cooperative transmission strategy. And aswe see in the simulation results, the 50% user through-put and 5% user throughput of cooperative transmis-sion strategy outperform eICIC method.

Figure 2: Users throughput CDF in differentcases

5. CONCLUSIONSIn this work, we have presented a cross-tier cooper-

ative transmission strategy in macro-pico HetNet. Wehave selected users distributed in range expansion areasand proposed a resource blocks allocation algorithm tosupport the cooperative transmission on resource blocklevel. Simulation results showed that the proposed strat-egy outperforms the original RE scheme and the exist-ing eICIC technology with range expansion in terms ofsystem performance.

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