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Energy Consumption Comparison Between MacroMicro and Public Femto Deployment in a Plausible LTE Network ∗
"... We study the energy consumptions of two strategies that increase the capacity of an LTE network: (1) the deployment of redundant macro and micro base stations by the operator at locations where the traffic is high, and (2) the deployment of publicly accessible femto base stations by home users. Prev ..."
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We study the energy consumptions of two strategies that increase the capacity of an LTE network: (1) the deployment of redundant macro and micro base stations by the operator at locations where the traffic is high, and (2) the deployment of publicly accessible femto base stations by home users. Previous studies show the deployment of publicly accessible residential femto base stations is considerably more energy efficient; however, the results are proposed using an abstracted model of LTE networks, where the coverage constraint was neglected in the study, as well as some other important physical and traffic layer specifications of LTE networks. We study a realistic scenario where coverage is provided by a set of nonredundant macromicro base stations and additional capacity is provided by redundant
Energy Saving and Capacity Gain of Micro Sites in Regular LTE Networks: Downlink Traffic Layer Analysis
"... We study the impact of deployment of low cost, low power micro base stations along with macro base stations on energy consumption and capacity of downlink LTE. We add three important elements to the existing studies: a traffic layer analysis that take both the physical and traffic layer specificatio ..."
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We study the impact of deployment of low cost, low power micro base stations along with macro base stations on energy consumption and capacity of downlink LTE. We add three important elements to the existing studies: a traffic layer analysis that take both the physical and traffic layer specifications of LTE downlink into account; a thresholdbased policy to associate users to base stations; and an allocation scheme to allocate the frequency band to macro and micro sites. We investigate all combinations of these elements through numerical evaluation. We observe that 1. there are important differences between traffic layer and physical layer analysis, 2. thresholdbased user association policy improve the capacity of the network by up to 33 % without affecting the energy profile of the network, and 3. considerable energy saving and capacity gain can be achieved thought an optimal allocation of the frequency band to macro and micro sites. Finally, we show that up to 46 % saving in energy can be achieved by a careful network deployment as compared to the case that no micro sites are deployed in the network. I.
Flowlevel Modeling and Optimization of Intercell Coordination with Dynamic TDD
"... ABSTRACT We study the intercell coordination problem between two interfering cells combined with dynamic timedivision duplexing (TDD). In dynamic TDD, each station selects in each time slot whether it is serving uplink (u) or downlink (d) traffic. Thus, the system has four possible operation modes ..."
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ABSTRACT We study the intercell coordination problem between two interfering cells combined with dynamic timedivision duplexing (TDD). In dynamic TDD, each station selects in each time slot whether it is serving uplink (u) or downlink (d) traffic. Thus, the system has four possible operation modes (uu, ud, du, dd). The amount of intercell interference between the stations clearly depends on the operation mode. We consider a flowlevel model where traffic consists of elastic data flows in both cells (cells 1 and 2) and in both directions (uplink and downlink). We first characterize the maximal stability region, and then determine the optimal static (i.e., stateindependent) policy. Our main objective is to analyze the potential gains from applying dynamic (i.e., statedependent) policies, where the chosen operation mode depends on the instantaneous state of the system. To this end, motivated by certain stochastic optimality results in the literature, we define several priority policies. As a reference policy, we have the wellknown maxweight policy, and we also develop another dynamic policy by applying the policy iteration algorithm. Notably we prove that certain simple priority policies are, in fact, stochastically optimal in some special cases, but which policy is optimal depends on the setting. To study the exact performance gains achieved by the dynamic policies, we perform extensive simulations. While our stochastic optimality results require exponential service times, in the simulations, we also study the impact of nonexponential service times and consider a physical model where the service time distribution is determined by the joint distribution of flow sizes and the random location of the corresponding user in the cell area. The maxweight policy is, as expected, performing well but the various priority policies are sometimes better and even optimal. Jointly the results indicate that dynamic policies give significant performance gains compared with the optimal static policy.
Minimizing file transfer delays using SRPT in HSDPA with terminal constraints
"... Abstract—In an HSDPA system, multiple users are scheduled in a time slot due to constraints on the user terminals with respect to how many codes a particular user can utilize. We model the allocation of the codes at the socalled flow level. This results in a particular multiserver queuing model, wh ..."
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Abstract—In an HSDPA system, multiple users are scheduled in a time slot due to constraints on the user terminals with respect to how many codes a particular user can utilize. We model the allocation of the codes at the socalled flow level. This results in a particular multiserver queuing model, where codes correspond to servers and multiple servers are allocated per flow subject to constraints on the maximum number of codes. In this context, we focus on minimizing the mean flow delays by utilizing flowlevel information on the remaining service times. While SRPT is the optimal policy for minimizing the mean delay in an M/G/1 queue, no such optimality results exist for the dynamic setting in multiserver models. We derive a heuristic SRPT policy for the system and evaluate its performance against the fair roundrobin policy, which can be modeled at the flowlevel as a processor sharing system. The results demonstrate that using SRPTlike scheduling can significantly decrease the overall mean delays, as well as the conditional delays. Index Terms—flowlevel analysis, multiserver models, sizebased scheduling, SRPT, cellular networks, HSDPA I.
Professorship: Networking Technology Code: S38
"... Optimal intercell coordination for elastic ..."
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"... Schedulerdependent intercell interference and its impact on LTE uplink performance at flow level ..."
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Schedulerdependent intercell interference and its impact on LTE uplink performance at flow level