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... Duplex (FDD), as shown in Figure 4, implies that uplink and downlink transmissions take place in different and sufficiently separated frequency bands. ...
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... Duplex (TDD), as shown in Figure 4, implies that uplink and downlink operate in different non-overlapping time slots. ...
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... the (Macro + Pico) case has a higher cell edge throughput than the (Macro+Pico+RE) case which shows that using range extension without ABS is not effective as range extension users suffer from a high interference level from the Macro-eNB. Finally Figure 40 shows the normalized throughput per user for the 4 cases it can be seen that the 3 cases having the Pico-eNB layer have almost equal throughput while the Macro-eNB only case has a very low normal throughput. ...
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... 43 shows the cell edge users in the ABS=90% case and it shows that all the cell edge users are Macro-eNB users. Figure 44 represents the throughput CDF for the 11 cases, it can be seen that the ABS=20% case has the highest throughput for the first 10% users and maintaining a moderate throughput for the rest of the users while for the ABS=90% case it has the lowest throughput for the first 30% users, which are mostly Macro-eNB users, while it has the highest throughput for the 40% to 95% users and since the main criteria to optimize is the cell edge throughput it is very obvious that the optimum ABS value is 20% as given by the formula in (31). ...
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... calculating the optimum ABS ratio according to eq. (31) gives which can be rounded to . Figure 45 represents the normalized cell edge users throughput for the different ABS configurations, as can be seen the best cell edge throughput is given for ABS percentage=70% which is 26.29% higher than the no range extension case. Calculating α using equation (51) gives , which has lower cell edge users throughput (-18%) than the value calculated using equation (31). ...
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... α using equation (51) gives , which has lower cell edge users throughput (-18%) than the value calculated using equation (31). Normalized cell-edge user throughput bps/Hz/user Figure 46 represents the normalized user throughput and it shows that the ABS=70% case has a relatively high normalized throughput which is 3.2% higher that the no range extension case. Figure 47 represents the throughput CDF for all the cases and we can see that the ABS=70% case maintains a very good throughput for almost 75% of the users which clearly shows that this case is the optimal one. ...
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... cell-edge user throughput bps/Hz/user Figure 46 represents the normalized user throughput and it shows that the ABS=70% case has a relatively high normalized throughput which is 3.2% higher that the no range extension case. Figure 47 represents the throughput CDF for all the cases and we can see that the ABS=70% case maintains a very good throughput for almost 75% of the users which clearly shows that this case is the optimal one. [%] ...
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... range extension No ABS ABS: 10% ABS: 20% ABS: 30% ABS: 40% ABS: 50% ABS: 60% ABS: 70% ABS: 80% ABS: 90% values of α according to equation (31) (blue line) and the optimal α according to simulations (green line) are almost the same, while the α values according to equation (51) (orange line) are quite far from the optimal values. Figure 49 represents the throughput values for the 3 results of α, same as Figure 48 but the y-axis represents the throughput not the ABS ratio, and it can be seen that the throughput resulting from the values of α according to equation (31) Optimal ABS ratio according to the formula(total nrof RE ues) ...
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... range extension No ABS ABS: 10% ABS: 20% ABS: 30% ABS: 40% ABS: 50% ABS: 60% ABS: 70% ABS: 80% ABS: 90% values of α according to equation (31) (blue line) and the optimal α according to simulations (green line) are almost the same, while the α values according to equation (51) (orange line) are quite far from the optimal values. Figure 49 represents the throughput values for the 3 results of α, same as Figure 48 but the y-axis represents the throughput not the ABS ratio, and it can be seen that the throughput resulting from the values of α according to equation (31) Optimal ABS ratio according to the formula(total nrof RE ues) ...
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... comparison is done for 6 different range extension values. Figure 54 and Figure 55 show that the theoretical results, equation (31), are very close to the optimal ones, while the results of equation (51) give worse results than those of equation (31). ...
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... 62 illustrates the cell edge throughput for the 4 dB range extension and it shows that the suboptimal solution (ABS= 20%) is very close to the optimal solution (ABS=30%). It is worth mentioning that the α values resulting from equation (51) Figure 64 show that the ABS ratio values and the resulting throughput according to equation (31) give the optimal ABS ratio in all cases except in the range extension 12 dB and 16 dB where it gives the suboptimal solution but still the results are better than the ones resulting from equation (51). Figure 65 illustrates the cell edge users normalized throughput for the range extension=16 dB case and it shows that the ABS ratio given by the formula (ABS=0.7) is the closest to the optimal value (ABS =0.6) . ...
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... we consider the optimized value of the ABS ratio according to equation (31) (ABS=70%) we see that it has a high cell edge users normalized throughput in Figure 67 and a high normalized throughput as well in Figure 68. Also considering the throughput CDF in Figure 69 that shows the ABS=70% case and the following 2 cases having the best throughput for the first 70% of the users and if we compare that to the case when we used a range extension of 4 dB in section 5.3.3.1 where the optimized value of of the ABS ratio (20%) had the highest throughput for only 40% of the users in Figure 44. No This shows that if we compare the optimum ABS ratio cases for different range extension values we find that having a higher range extension value gives higher normalized throughput value. ...
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Citations
... Since these muted subframes are not totally blank they are called Almost Blank Subframes (ABS). The basic idea is to have some subframes during which the macro-eNB is not allowed to transmit data allowing the range extension pico-eNB users, who were suffering from interference from the macro-eNB transmission, to transmit with better conditions [32]. ...
Heterogeneous networks (HetNets) are proposed in order to meet the increasing demand for next generation cellular wireless networks, but they also increase the energy consumption of the base stations. In this paper, an activity management algorithm for improving the energy efficiency of HetNets is proposed. A smart sleep strategy is employed for the operator deployed pico base stations to enter sleep and active modes. According to that strategy, when the number of users exceeds the turn on threshold, the pico node becomes active and when the number of users drop below the turn off threshold, it goes into sleep mode. Mobile users dynamically enter and leave the cells, triggering the activation and deactivation of pico base stations. The performance of the system is examined for three different cellular network architectures: cell on edge (COE), uniformly distributed cells (UDC) and macro cell only network (MoNet). Two different user distributions are considered: uniform and hotspot. The effects of number of hotspot users and sleep energies of pico nodes on the energy efficiency are also investigated. The proposed activity management algorithm increases the energy efficiency, measured in bits/J, by $20\%$. The average bit rates achieved by HetNet users increase by $29\%$ compared with the MoNet architecture. Thus, the proposed activity control algorithm increases the spectral efficiency of the network while consuming the energy more efficiently.
... The Enhanced Inter-Cell Interference Coordination (eICIC) proposal in LTE standards serves two important purposes: allow for time-sharing of spectrum resources (for downlink transmissions) between macros and picos so as to mitigate interference to pico in the downlink, and, allow flexibility in user equipament (UE) association so that picos are neither underutilized nor overloaded [2][3][4] [7]. ...
... The relevant previous work focused on studying the influence CRE parameters on the performance and find optimal values for ABS ratio [2]. ...
... GA search parallel from a population of points. Therefore, it has the ability to avoid being trapped in local optimal solution Macro cell radius 500 m [2] Pico cell radius 50 m [2] Macro-eNB transmit power 43 dBm [6] Pico-eNB transmit power 38 dBm [6] Macro cell pathloss model 128.1 + 37.6 log10(d) [6] Pico cell pathloss model 38 + 30 log10(d) [6] Shadowing std. dev. ...
... The previous section intensifies the potential need of managing the severe interference in the downlink [6], resulting from the CRE in the MNB-PNB deployment scenario. The almost blank subframe (ABS) [7], [8] is the key approach to time domain interference mitigation in LTE-Advanced. ...
This paper presents the interference mitigation for co-channel deployments of pico-cells (PNBs) and macro-cells (MNBs). We address the issue of downlink interference by MNBs to PNBs user equipment (UE), especially the UEs offloaded via cell range extension (CRE) bias, who suffers severe interference from MNBs. Interference mitigation technique based on time domain muting (TDM) of resources by MNBs is presented here. The interference level varies significantly with RE bias, hence, there has to be optimized muting of resources as a function of MNB UEs and PNB CRE bias UEs. This ensures how much resources to be muted by each MNB so that resources are not wasted and for interference mitigation to be achieved. This decentralized approach of muting performs near optimal, when compared with the ideal and centralized muting pattern.
Enhanced inter-cell interference coordination (eICIC) is one of the most popular techniques for mitigating interference because it has only a few backhaul requirements in heterogeneous networks (HetNets). This chapter investigates the dynamic eICIC mechanism with quality of service (QoS) requirements in wireless communication systems. Because of user mobility and traffic dynamics, a dynamic eICIC mechanism is necessary in modern wireless networks. To address QoS requirements, a small cell must address the cell-association problem so that users can utilize the system resources more efficiently under the dynamic eICIC mechanism. Hence, we present a joint dynamic eICIC mechanism and admission control method to handle this problem. In contrast to the traditional eICIC mechanism, the proposed method does not add any backhaul requirements. In order to evaluate the system performance from different angles, throughput and fairness are selected as the metrics. We first use a modified sum-rate utility as the throughput metric and propose a dynamic eICIC strategy for the system sum throughput maximization. We then choose a proportional fairness (PF) utility as the fairness metric and propose a dynamic eICIC strategy for proportional fairness maximization. Finally, computer simulations show that the performance in various scenarios of the dynamic eICIC mechanism with QoS requirements is better than a static eICIC mechanism and the conventional dynamic eICIC mechanism.
An inter-cell interference coordination (ICIC) technique that recently has attracted interest is to create protected subframes to reduce inter-cell interference. This technique can under some circumstances lead to almost blank subframes (ABS) where there is interference only on the pilots but no interference on the data. This paper analyzes the performance of traditional MRC and IRC receivers for ABS subframes both analytically and through simulations. It is found that IRC often yields better performance than MRC even in the absence of interference on data making the IRC receiver an attractive receiver in practice.
