Interference Mitigation Strategies for WiMAX Networks Nicola Riato#1, Federico Serrelli*2, Andrea Sala#, Antonio Capone*3 #
Nokia Siemens Network SpA, Milano, Italy 1
[email protected]
*
Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano, Italy 2
[email protected] 3
[email protected]
Abstract—WiMAX IEEE802.16e systems are intended to provide high spectral efficiency in order to support services with challenging quality of service constraints in heterogeneous scenarios. However, when addressing such goal, it is important to consider in detail the impact of deployment related issues that can affect relevantly the expected system performance. Inter-cell interference is a key aspect that limits system level performances. On the other side, WiMAX standard provides several useful features at both PHY and MAC layer for facing propagation channel impairment and that can be exploited in order to combat inter-cell interference. In this paper an analysis of the main features influencing the inter-cell interference scenario is provided and interference mitigation strategies are proposed and evaluated through system level simulations.
I. INTRODUCTION. The spectral efficiency maximization objective, that is at the base of all current and future mobile cellular system design, imposes to operate with the tightest possible reuse of time/frequency resources. As a result, inter-cell interference becomes one of the main elements affecting system performance. Mobile WiMAX systems, specified through the IEEE802.16e standard, [1], thanks to the OFDMA PHY and to the high degree of flexibility of specification, allow to implement diverse interference mitigation strategies that can rely either on inter-cell interference randomization or inter-cell interference coordination avoidance. In this paper two interference mitigation techniques for the forward link are proposed and implementation related issues are described and analysed through system level simulations. The paper is structured as follows: Section II provides a description of the main characteristics affecting interference scenario of a Mobile WiMAX system. In Section III, a two interference mitigation strategies are proposed. In Section IV the main assumptions for system level analysis are described, and the baseline interference scenario performance assessed. In Section V interference mitigation strategies are analysed and compared through simulations. In Section VI some conclusions are drawn. II. IEEE802.16E AND INTERFERENCE SCENARIO The IEEE802.16e is based on a OFDMA physical layer that provides multiplexing of data streams from multiple users onto the downlink sub-channels and uplink multiple access by
means of uplink sub-channels. Downlink multiplexing and uplink multiple access are realized by allocating timefrequency resource blocks, called slots, to distinct users. Slot structure, defined in terms of frequency resources (subchannels) and time resources (OFDM symbols), depends on the particular subcarriers permutation rules applied out of those provided by the standard. The focus of this analysis has been posed on the DL PUSC distributed permutation rule, that are intended for providing frequency diversity and inter-cell interference averaging effects.. The DL PUSC permutation is characterized by the parameter DLPermBase (DLPB), an index determining the mapping of physical subcarriers onto subchannels. This parameter determines the subcarrier overlapping probability within interfering sectors of the network. Basically, two interference scenarios can be identified according to two different settings of the DLPB parameter: • Same DLPermBase in all cells (SameDLPB scenario): in this case, the same subcarrier permutation rule is applied all over the network. This results in a deterministic superposition of logical resources (slots), i.e. subchannels will be composed of the same subcarriers sets in all interfering cells. In this deployment, permutations provide only frequency diversity over the channel bandwidth. • Distinct DLPermBase in all cells (DistinctDLPB scenario): permutations, in this case, distribute randomly the subcarriers independently from site to site. Interference will result to be spread all over the channel bandwidth (the same subchannel in two interfering sectors will be composed by a different set of physical subcarriers). The interference level suffered by users will be related mainly to the subcarrier overlapping probability that is directly related to the network load (i.e. number of subchannel used in each frame). The standard provides several features that are useful for struggling propagation impairments and that can be exploited for interference mitigation purposes, both at physical and MAC layer. In this paper, we propose and evaluate, through system level simulations, interference reduction strategies based on the joint exploitation of MAC layer procedures, such as power boosting control, dynamic subchannels allocation strategies and load control. III. INTERFERENCE MITIGATION STRATEGIES
Efficient interference mitigation can be obtained through the coordination of several MAC layer procedures, such as frame mapping, admission control, and power control. In fact, the standard provides the possibility to separately control the power applied to the transmission of each DL Burst in DL subframe. Available boosting factors spans values from +9dB to -12dB in steps of 3dB. In this Section, two strategies are proposed and investigated. The former called ‘Soft Strategy’, suited for DistinctDLPB scenario, is based on a combination of interference randomization provided by permutation and power boosting. The second, called ‘Soft Reuse-9’, is based on soft frequency reuse scheme [5,6,7], that foresees the application of restrictions to the usage of downlink resources both in terms of time/frequency resources and transmit power resources. A. Soft Strategy The Soft Strategy relies on power reduction for enhancing the interference mitigation obtained through permutation randomization. The Soft Strategy, exploiting the dependence of interference form cell load, operates as a distributed admission control policy that aims at minimizing the interference power within the network. For each incoming user, the SINR on preamble field is evaluated. On the base of this measure, the maximum power reduction, i.e. minimum power boosting factor (BF), such that QoS requirements are satisfied. The Modulation and Coding Scheme (MCS) corresponding to SINRpreamble plus the selected BF finally is associated to the user. If enough resources are available for user’s data allocation with the selected MCS, within a convenient number of frames, the user is admitted to service. In such way, each data allocation will occupy the largest set of resources but the minimum power will be used for transmission. Furthermore, interference averaging effect of permutations will spread the interference power over the channel bandwidth thus reducing the impact over critical users. In case resources for the incoming user are not available, the admission control will try to increase the power of already allocated users starting from those experiencing the highest values of SINR on preamble. The MCS will be scaled according to the expected SINR value plus the updated boosting factor. The frame occupation will be correspondingly reduced. Users will be finally blocked if not enough resources are available at the end of all possible MCS scaling. Soft Strategy requires that the frame mapping procedure allocates each DL Burst using the minimum number of subchannels of the DL subframe. In such a way a twofold advantage can be obtained: on one side, the number of full power subcarriers is minimized during the mapping procedure, on the other side data allocation with reduced power are spread along the time dimension providing an even distribution of interference over time. B. Soft Frequency Reuse - Soft Reuse-9: Soft Frequency Reuse schemes aim at granting to critical users, i.e. experiencing a low SINR on preamble, to perceive a reduced interference level on data allocation. In order to reach
such objective, Soft Frequency Reuse schemes foresee the application restrictions to the usage of downlink resources e.g. time/frequency resources and transmit power resources. We describe a Soft Frequency Reuse scheme, called Soft Reuse-9, suited for SameDLPB scenario. It is implemented by dividing the subchannels in the DL subframe into three sets and by applying a proper power reduction factor, chosen between 0, -3 and -6 dB, to each subchannel set. A sort of power mask is applied to the subchannels of the DL subframe. The coordinated application of the power masks to all the interfering sectors of the network as shown in Figure 1, will provide a differentiation of the interference level within each of the subchannel sets. In particular, a protected subchannel set, that characterized by the 0dB boosting factor, is individuated. In fact, in each subchannel of this set, all the first ring interferers will transmit with reduced power, thus providing a relevant reduction of the interference in respect of that experienced on preamble field. On the other side, an increased interference level is expected to be perceived on the other subchannel sets (with boosting with -3 and -6 dB) because of the reduction of the useful signal. Sub-ch set 2 Sub-ch set 1
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Figure 1. Soft Reuse 9 deployment.
The strategies proposed above have been compared by means of system level simulation that allowed the analysis of their interaction with the involved MAC layer procedures and to obtain a detailed evaluation in terms of coverage, throughput and outage probability and. IV. SYSTEM LEVEL SIMULATION MODEL System level performance has been evaluated through a dynamic system level simulator compliant to the standard IEEE 802.16e-2005, implemented on ns-2.29 simulation platform. A. Network Topology Model The WiMAX network has been modeled using a three tier hexagonal cellular network with 19 cells, each with 3 sectors. An underline frequency reuse 3 scheme (Reuse-3), referring to three mutually exclusive frequency allocations one per sector of a cell, has been assumed. Table I lists the main parameters of the network topology model. According to preliminary link budget calculation, the inter-site distance has been set to 900m. B. Propagation and Interference Model All system level simulations have been carried out assuming a urban macro-cell environment for modeling the
TABLE I PHYSICAL LAYER PARAMETERS Parameter Value Number of sites 19 (two interference rings) Number of sectors per site 3 BS-BS distance 0.9 km Center frequency 2.5 GHz Reuse scheme Reuse-3 Total channel bandwidth 15 MHz Channel bandwidth per sector 5 MHz NFFT 512 Frame duration 5 ms OFDMA G parameter 1/8 BS PHY model BS Tx power/sector 40 dBm BS antenna height 30 m BS antenna pattern 65° (-3 dB) with 50 dB front-toback ratio BS antenna gain 17.5 dBi TS PHY model TS antenna height 1.5 m TS antenna pattern Omnidirectional TS Noise Figure 7 dB TS mobility fixed
long term characteristics of the wireless channel. In particular COST 231 HATA pathloss model has been assumed and shadowing, shaped as a lognormal random variable with zero mean and standard deviation of 8 dB, has been simulated. An idealized AWGN channel model has been considered in place of a more realistic stochastic channel model. This choice relies on the assumption that link adaptation algorithm is able to track and compensate for short term channel fluctuations while the frequency selectivity is averaged out by the DL PUSC permutation rule. At the same time, this modeling assumption allows to isolate the impact of inter-site interference on system level performance and to evaluate interference averaging effect provided by the DL PUSC permutation. The simulator allowed to deterministically evaluate the interference with subcarrier resolution. DL PUSC permutation rule has been implemented according to the standard specification with the possibility to set the permutation index independently per each BS. The link performances are taken into account at system level through a PHY abstraction model based on the EESM (Exponential Effective SINR Mapping) approach [2]. Given the simplified AWGN assumption, the frequency selective nature of the perceived SINR over subcarriers of each OFDMA symbol is caused only by interference. The used PHY performance metric are SLER (Slot Error Rate) performance curves versus SINR obtained from Link Level simulation in AWGN condition. C. MAC Layer Model Tests and simulations have been conducted considering the UGS service class simulated as VoIP sources without silence suppression (codec G.728). The VoIP service class has been chosen because of the strict QoS requirements posed in terms of information loss (PER
