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Volume 2, Number 2, December 2011 Journal of Convergence Dynamic Frequency Reuse Factor Choosing Method for Self Organizing LTE Networks

Modar Safir Shbat Vyacheslav Tuzlukov College of IT Engineering, EE Department College of IT Engineering, EE Department Kyungpook National University (KNU) Kyungpook National University (KNU) Daegu, South Korea Daegu, South Korea [email protected] [email protected] `

Abstract— Under the development of the self organizing network convergence networks [2]. This paper investigates the radio (SON) for long term evolution (LTE) systems, the radio resource resource management considerations, the possible frequency management (RRM) with suitable frequency reuse technique is a reuse solutions, and the main geometry factor principles; and vital factor in providing the required performance for future presents a new concept for the feedback about the channel applications especially in the case of convergence of networks and quality that should be sent from the UE to the eNodeB in order services. A way to improve the scheduling process of the physical to replace the geometry factor, and reduce the complexity and radio resource blocks (PRBs) should be considered to increase the scheduling processing load. The rest of this paper is the network throughput and to achieve better quality of service organized as follows: the LTE network RRM considerations (QoS) and fairness to the users. In this paper, some important are discussed in Section II. Section III introduces the geometry aspects related to RRM are discussed, and a new channel quality factor concept for the frequency reuse employment. A suitable indicator (CQI) concept based on a simple feedback technique is presented. This method creates an alternative vision for the radio resource scheduling algorithm is explained in section IV. geometry factor to employ the selective frequency reuse The introduced concept general analysis is presented in Section technique inside the network cells. V. The conclusion remarks are discussed in Section VI.

Keywords- Long Term Evolution (LTE) Networks; Radio II. RRM IN LTE NETWORKS Resource Management (RRM); Frequency Reuse Factor (FRF); Geometry Factor. In 3GPP LTE systems, OFDMA for downlink and SC- FDMA for uplink are accepted as multiple access techniques. Radio resource scheduling is a process in which the resource I. INTRODUCTION blocks are distributed among UEs. None of the PRB scheduling The self organizing network (SON) tasks and standards for algorithms can solve all existing problems associated with the long term evolution (LTE) systems are essentials in the maximum number of users with available transmission services, broadband mobile data demand of the upcoming applications. or the limited and imperfect channel information used at the BS, The main target of the recent research is to increase the QoS, and fairness problems. Before assigning the modulation valuable spectrum efficiency, maximize the total capacity, technique and coding rate for UE by eNodeB, the eNodeB improve the QoS, and satisfy the service convergence performs scheduling on available physical radio blocks (PRB) management requirements [1]. All the mentioned targets and and informs the UE about their allocated time/frequency more can be achieved by flexible and effective spectrum resources and transmission formats to be used by the user. PRB allocation and a physical radio resource blocks (PRBs) scheduling is based on UE capability, QoS, fairness, frequency scheduling scheme, with a simple and fast feedback scheme for reuse factor, inter cell interference (ICI), and measurement the channel quality condition. Radio resources are scheduled reports from the UE, and according to the latest trend in the every 1ms in the 3GPP LTE network and different frequency wireless technologies, the networks and service convergence bandwidths and/or aggregated bandwidths can be assigned to required an additional load and considerations for the RRM or an individual user based on the channel condition and radio scheduling algorithm (vertical handover VHO). The main availability. Due to the rapidly and instantaneously changing idea to employ a frequency reuse is to assign the same nature of radio channel quality, we should have a sufficiently frequency band in different cells that are usually far from each fast scheduling algorithm to compensate for the changeable other to avoid high interference between neighbouring cells. channel condition. Right before assigning the modulation We can significantly improve the signal-to-interference-noise technique and coding rate to user equipment (UE) by the ratio (SINR) without using the same frequency band for eNodeB (the base station BS in the LTE network), and based neighbouring cells [3]. Unfortunately, this improvement in on the transmission channel condition, appropriate physical SINR causes a reduction in the available spectrum per cell. The radio resource blocks (PRBs) must be allocated based on the system capacity can be estimated using Shannon’s formula [4]: RRM technique used. Thus, the problem of scheduling and distribution of the PRBs in 3GPP LTE among users is a complicated process. Speeding up the scheduling process is an BW TPk  log2 (1 SINRk ), (1) important point in the way to achieve the proposed standard of K PRBs scheduling time without any sacrifices in other important network requirements like the fairness and security, especially where k is the reuse factor meaning that only 1/kth part of the in the case of converged different wireless networks or service spectrum can be used by a single cell, BW is the LTE total

bandwidth in Hz, and SINRk is the SINR with reuse k. SINR is subchannel used by CCU, and P is the reference power given by [5]: signifying the uniform transmitted power used by each subchannel in a classical reuse-1 system. We can see that when α equals 1, P is equal to P , and the SFR is a reuse-1 Pr CCU CEU SINR  , system. As α → ∞, P and P will converge to 0 and 3P, P  P  N (2) CCU CEU intracell intercell 0 respectively, and the SFR becomes a reuse-3 system. where Pr is the received power density from the user, Pintracell is the interference that comes from users inside the cell, Pintercell is the interference from neighbouring cells, and N0 is the noise power.

III. FREQUENCY REUSE AND ALTERNATIVE GEOMETRY FACTOR CONCEPT In order to have a beneficial frequency reuse, an appropriate tradeoff between the bandwidth and SINR is important to utilize the spectrum efficiently by setting a proper value for frequency reuse factor (FRF) in order to maximize the cell/user throughput. The frequency reuse factor should be chosen according to intercell interference power, which depends on the cell size. Powerful interference favours a high Figure 1. Concept of the SFR scheme in LTE network. reuse factor and vice-versa. In this paper, a soft frequency reuse (SFR) is used. This technique consists of splitting the The introduced SFR scheme (also called reuse 1/3) has low bandwidth into two parts, namely the full reuse (FR) and complexity and good performance for CEUs. Additionally, it partial reuse (PR) parts. The FR part uses a reuse factor equal has two main drawbacks, namely the signalling overhead and to 1 and the PR part is allocated to the cell edge-users. This overall loss of throughput. In the next section, we try to structure allows us to have a two level allocation scheme overcome these drawbacks. (TLA), where the first level is the cell-level resource Since the channel quality information (CQI) has to be allocation (CRA) and the second level is the user-level available at BS (eNodeB), the feedback information can be resource allocation (URA). It means that the cell users are used for partitioning users. Another important topic here is the divided into two categories, namely the cell centre user (CCU) required number of feedback bits to cover and achieve the and the cell edge user (CEU). This classification can be done optimal scenario for the LTE system and, additionally, to using the geometry factor G: reduce the signalling overhead problem. The number of feedback bits is the indicator of the feedback quality and is Pserve used by the BS (transmitter) to define the served users from G  , (3) N  Pnonserve the total number of users sending feedback to the BS. Based on the previous statement, we see that to apply any kind of where P is the total power generated by the connected BS, scheduling scheme there is a need to evaluate the feedback serve quality and to decide if the user should be served or not. In P is the total power received from all BSs served as the nonserve this case, the less the number of the feedback bits the less interference sources, and N is the portion of the power from complexity and the best stability there is in the scheduling BSs that can be modelled as AWGN. model. Soft frequency reuse (SFR) is the applying frequency reuse In the proposed solution of this paper, each eNodeB factor (FRF) of 1 for CCUs and FRF of 3 to CEUs [6]. One receives only one bit from each user instead of the full third of the whole available bandwidth named the major information about SINR (in the case of the MIMO system, UE segment can be used by CEUs where the packets should be sends information about the SINR for the best beam of every sent with higher power. CCUs can access the entire physical antenna element and this feedback consists of radio resources with lower transmission power. To realize an N  N numbers). This bit indicates whether the SINR FRF of 3 for CEUs, the major segments among directly real integer neighbouring cells should be orthogonal (Fig. 1). The power of the receiving antenna is over a given value (threshold) or allocation for each type of users can be determined as: not. Now, the transmission by M beams of the BS transmitter is carried out using a single bit of feedback from each user which measures the SINR and compares it with a S P 3P PCCU   , (4) predetermined constant threshold  . The threshold is ( 1) T  S   2 considered as a network parameter known by the BS and all users. The only bit (“0” or “1”), as a feedback from the user, PCEU   PCCU , (5) can inform the BS whether the SINR exceeds the threshold value or not. For the pre-introduced LTE system, this where S is the total number of subchannels in the LTE system, threshold can be adjusted to indicate the CCUs at SINR T is the number of available subchannels for the CEUs, α is the > (“0”), otherwise to indicate the CEUs at SINR < (“1”). power ratio between the subchannel used by CEU and the Another scenario is to use two thresholds, 1 in the case of “0”

feedback bit and CCUs, and  2 in the case of “1” feedback bit ( Ntotal ). This admission criterion can be presented in the and CEUs. After receiving the previous simple feedback from following form: all users, the BS schedules a radio resource block or blocks for each user. The presented method is simple and ensures an k effectiveness to decrease the signalling complexity of the  Nm  Nnew  Ntotal. (10) network. By this method, we can see that the UE helps to i1 replace the geometry factor by using simple feedback to indicate whether it is a cell centre or edge user, and also the IV. SUITABLE RADIO RESOURCES SCHEDUALING alternative concept reduces the processing load in the ALGORITHM eNodeBs in the scale of the required time to define the G value [7]. The value of the suggested threshold  can be the For the presented new concept, it is possible to implement effective SINR that used to obtain transport radio blocks. The different kinds of radio resource scheduling techniques. Here, effective SINR can be defined by performing nonlinear one simple and suitable algorithm out of these techniques is going to be employed. averaging of the several available physical radio resource blocks (PRBs) as follows: This scheme is proposed with the aim of reduction of frequency selective scheduling gain loss and to increase the SINR  N  i  data rate at the cell edge. By this algorithm the frequency  1   reuse factor is 1 at the centre and 3 at the edge of the cell   SINReff   ln e , (6)  N  (SFR). The frequency scheduler is working in a way such that  i1  the cell edge’s users have a higher probability of using the frequency band with higher power and the cell centre’s users where N is the total number of sub-carriers to be averaged, have a higher probability of using the frequency band with and  is calibrated by means of link level simulation to fit the lower power. Here the priority for each (k-th) user at each compression function to the additive white Gaussian noise resource block should be calculated first, and then the user (AWGN) block error ratio. will be assigned with the (j-th) resource block at time (t) using This model introduces the binary user/resource block the following simple formula: assignment variable x that is “1” if the user m obtains resource block r and “0” otherwise. The expected throughput of the RDR (t) P (t)  kj (11) user m using the block r depends on the expected SINR. The kj R (t)F expected SINR is derived from the latest SINR measurement. k kj Thus, the expected throughput can be presented in the following form: where RDRkj (t) is the requested data rate for the k-th user over

the j-th RB in time (t), Rk (t) is the low-pass filtered averaged   (7) data rate of the k-th user, and F is the priority factor and can THRm,r  f log2 (1 SINRm,r ) , kj take a value between 0 and 1 among the following cases: where f is the resource block bandwidth. For the QoS User k at cell centre, RB j is with low power criterion, we should take into account the guaranteed bit rate User k at cell centre, RB j is with high power (GBR) as the only criterion under different services. Based on User k at cell edge, RB j is with low power the user’s GBR and CSI, the required number of PRBs for User k at cell edge, RB j is with high power each user can be determined as [8]: Giving different values to j is the way of controlling the resource assignment to users in the edge and centre of the cell. GBRm Nm  , (8) The value of is estimated by using AMC (Adaptive M BWPRB Sm Modulation and Coding) selection which is dependent upon current transmission channel condition. In the case of data

retransmission, the has a different value to the one Sm  log2 (1 SNIRm ) , (9) for a new user request in order to guarantee a successful transmission; for that the estimated from is: where SNIRm is the average SINR for user m over the whole frequency band, Sm is the spectral efficiency of the user m, RDR (t)  R (SNR ) (12) BWPRB is the bandwidth of the PRB, M is the number of kj EF AC OFDM symbols in the PRB, and Nm is the required number of PRBs per TTI by the user m. The basic admission control where REF is the rate estimation function, and SNRAC is the criterion can be presented as the sum of PRBs per TTI accumulated signal to noise ratio over the transmission channel. required by new user requesting admission ( Nnew ) and the In any time interval of the scheduling process, the low-pass number of active users in the cell ( Nm ), and should be less filtered averaged data rate of any user is updated as than or equal to the total number of PRBs in the LTE system follows:

Rk (t 1)  (1 a)Rk (t)  aRDRk (t) (13) where a is the average rate window size, and RDRk (t) is the aggregate data rate for user k at time t. This scheduling technique is a modified version of the proportional fairness resource allocation algorithm and is called the softer frequency reuse based resource scheduling algorithm.

V. GENERAL DISCUSSION AND SIMULATION RESULTS There are three major frequency reuse techniques that can be used in LTE networks to cancel ICI effects, namely, the hard frequency reuse (HFR) with a fixed frequency reuse factor (1 or 3 are popular); the partial frequency reuse (PFR); and the soft frequency reuse (SFR) that is a part of the discussed technique in this paper. A simple LTE system level simulation [9] for the proposed system shows us that the SFR together with the new simple feedback and the user classification method has a good performance (Fig. 2) in terms Figure 3. The total throughput with the traffic load in the system. of total throughput in the cell for different values for signal-to- noise ratio (SNR) when there is no hybrid automatic repeat One more important issue is that the power control is request (HARQ) in the system (in the standards, LTE uses needed in the varying signal strength channel conditions to synchronous HARQ in the uplink while the downlink uses maintain the required SNR. The transmission power is asynchronous HARQ) or any other retransmission techniques. increased by the power controller at the BS in poor channel condition, and it decreases the transmission power in good channel conditions. The dynamic rate control is used for data services when constant data rate is not required but the SNR is much more important for the transmission, and it is well known that the dynamic rate control is inversely proportional to the power control. From this brief discussion, the strong relation between the power control and the radio resource scheduling and management in the LTE networks is obvious. The simulation results for the cell average sum power consumption with the proposed system show acceptable typical performance for the cell centre and cell edge users (Fig. 4).

Figure 2. SFR with the proposed system performance.

It is proposed in the 3GPP LTE networks that every 1 ms the radio resources in the cell should be scheduled. Thus, the way to speed up the scheduling process is essential and important. The SFR processing load is acceptable with good performance, especially for the cell edge users. Other frequency reuse schemes are introduced and some of them may have better performance than SFR, but there are some disadvantages in complexity and high processing load in the eNodeBs. The network traffic load type should be considered when the system throughput is presented for a specific physical radio resource scheduling technique. For the proposed system Figure 4. Average power consumption relation with the user distance. the network traffic for real time services such as voice calls is not taken into account; only the flexible data services are VI. CONCLUSIONS considered. Fig. 3 shows the network traffic load for the The proposed soft frequency reuse with the alternative downlink in the case of data transmission. concept for the geometry factor and user classification method

16 Copyright ⓒ 2011 Future Technology Research Association International Volume 2, Number 2, December 2011 Journal of Convergence is flexible, and can be employed in different radio resource [9] Josep Colom Ikuno, Martin Wrulich, and Markus Rupp, “System Level st scheduling and management techniques; for example, joint Simulation of LTE Network,” IEEE 71 Vehicular Technology Conference VTC2010, Taipei, Taiwan , 2010. radio resource management (JRRM), cognitive radio resource management (CRRM), and the dynamic fractional frequency reuse radio resource management scheme. The technique used in this paper (softer frequency reuse based resource scheduling algorithm with second frequency reuse factor equal to 3) is selected to perform the simulation for the system and show the efficiency of the proposed solution in terms of total throughput, traffic load for data transmission, and the average power consumption. SFR has a good performance, in both the average cell throughput and the cell edge user throughput. The proposed concept works to reduce the signalling overhead and speed up the scheduling process, employing the simple feedback method instead of the geometry factor to distinguish between the cell-centre users (CCUs) and cell edge users

(CEUs). Further improvement can be achieved by applying different PRB assignment methods in the form of semi-static versions of SFR, which means that the frequency resource configuration is adjusted on a time scale corresponding to a definite interval, which makes the resource partition adaptive to the traffic load variety. This procedure leads to a more complicated and higher signalling and proceeding load in the system. The effectiveness of applying the presented soft frequency reuse based on the geometry factor alternative concept has to be confirmed after deep analysis to be assured that we obtain a considerable improvement in the average scheduling delay (increase the scheduling speed) with equal or better cell average throughput.

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