Optimization method for the joint allocation of modulation schemes, coding rates, resource blocks and power in self-organizing LTE networks

Liu, David; Ladányi, Ákos; Jüttner, Alpár; Rivano, Hervé; Zhang, Jie

doi:10.1109/infcom.2011.5934888

Cited by 129 publications

(63 citation statements)

References 9 publications

(8 reference statements)

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“…We assume that the system uses adaptive modulation and coding with discrete rates. Table III taken from [18] and [19] gives us the mapping between the SINR and the efficiency (in bits/symbol) for the modulation and coding schemes (MCS) for LTE. The bit rate obtained by a user that has a SINR between level and level + 1 is r =…”

Section: A Parameter Settingsmentioning

confidence: 99%

Joint Resource Allocation and User Association for Heterogeneous Wireless Cellular Networks

Fooladivanda

Rosenberg

2013

IEEE Trans. Wireless Commun.

309

210

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Abstract-We propose a unified static framework to study the interplay of user association and resource allocation in heterogeneous cellular networks. This framework allows us to compare the performance of three channel allocation strategies: Orthogonal deployment, Co-channel deployment, and Partially Shared deployment. We have formulated joint optimization problems that are non-convex integer programs, are NP-hard, and hence it is difficult to efficiently obtain exact solutions. We have, therefore, developed techniques to obtain upper bounds on the system's performance. We show that these upper bounds are tight by comparing them to feasible solutions. We have used these upper bounds as benchmarks to quantify how well different user association rules and resource allocation schemes perform. Our numerical results indicate that significant gains in throughput are achievable for heterogeneous networks if the right combination of user association and resource allocation is used. Noting the significant impact of the association rule on the performance, we propose a simple association rule that performs much better than all existing user association rules.

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Section: A Parameter Settingsmentioning

confidence: 99%

Joint Resource Allocation and User Association for Heterogeneous Wireless Cellular Networks

Fooladivanda

Rosenberg

2013

IEEE Trans. Wireless Commun.

309

210

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“…Table III taken from [11], [12], [13], and [14] gives us the mapping between the SINR and the efficiency e for the modulation and coding scheme for LTE. In this table, there are 15 levels, let be such a level.…”

Section: Sinr Of Usermentioning

confidence: 99%

“…For example, in [11], the values of SC ofdm , SY ofdm , T subframe , and sub-channel bandwidth are 12, 11, 1ms, and 180KHz, respectively. In this study, we normalize the rates to θ for simplicity, since this normalization does not affect the results.…”

Section: Sinr Of Usermentioning

confidence: 99%

Joint channel allocation and user association for heterogeneous wireless cellular networks

Fooladivanda

Daoud

Rosenberg

2011

2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications

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Abstract-We study the engineering of heterogeneous cellular networks composed of a macrocell and some picocells by investigating the interplay of different network processes and parameters such as channel allocation, user association and reuse pattern (to control inter-cell interference between picocells). We formulate a joint association, channel allocation, and intercell interference management problem that relies on very few assumptions. This problem turns out to be an Integer Non-Linear program that is NP-hard. However, its structure is such that we can solve it exactly for relatively large size systems. We use optimal solutions as benchmarks to understand how different simple association schemes perform. Our results show the critical impact of the association rules on system performance and shows the interplay of the different processes and parameters. We believe that these insights will help design online association schemes in the future.

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“…We assume adaptive modulations with discrete rates such that whenever the SINR lies between any two thresholds, in Table 2, the rate f (P t,c n G c sn /(N 0 + I t,c sn )) obtained by the UE on that channel is the corresponding efficiency multiplied with SC OF DM SY OF DM /T subf rame [18]. Similarly, given N s , the optimal uplink scheduling at a …”

Section: Optimal Schedulersmentioning

confidence: 99%

“…∀n ∈ Ns, (18) where I t,c ns represents the interference on channel c seen by the BS due to UEs other than UE n operating on the same channel in the nearby cell sectors (represented by an expression similar to (12)) at time t and is a function of the BSS pattern and the scheduling at each of the interfering BSs.…”

Section: Optimal Schedulersmentioning

confidence: 99%

Energy and Throughput Trade-Offs in Cellular Networks Using Base Station Switching

Kumar

RosenbergLtoXtagsroleFellow

2016

IEEE Trans. on Mobile Comput.

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Abstract-Base station operation consumes a lot of energy, a considerable amount of which can be saved by switching off base stations during low user demand (for example, at night). Base station switching (BSS) can result in loss in coverage if not performed properly. We show that coverage is closely related to scheduling via power management and that the bottleneck is typically the uplink. To save energy, we propose a set of BSS patterns, at a global system-level, that have the potential to provide full coverage if the appropriate schedulers are used. We further show that the existing benchmark uplink scheduling schemes do not provide full coverage when BSS is used in urban as well as rural macro-cell environments (the downlink benchmark scheduling scheme provides full coverage only for some of the BSS patterns). Hence, we propose novel scheduling schemes for both uplink and downlink that realistically model interference, ensure full coverage, and provide good energy-performance trade-offs for the proposed BSS patterns. We also present a low complexity high performance heuristic for the proposed uplink scheduler. Finally, we show the presented models and results can be used to quantify, offline, the energy-performance trade-offs under different operating scenarios.

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Optimization method for the joint allocation of modulation schemes, coding rates, resource blocks and power in self-organizing LTE networks

Cited by 129 publications

References 9 publications

Joint Resource Allocation and User Association for Heterogeneous Wireless Cellular Networks

Joint Resource Allocation and User Association for Heterogeneous Wireless Cellular Networks

Joint channel allocation and user association for heterogeneous wireless cellular networks

Energy and Throughput Trade-Offs in Cellular Networks Using Base Station Switching

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