On the Accuracy of the Wyner Model in Cellular Networks

Abstract-Space-Time Network Coding (STNC) is a timedivision multiple access (TDMA)-based scheme that combines network coding and space-time coding by allowing relays to combine the information received from different sources during the transmission phase and to forward the combined signal to a destination in the relaying phase. However, STNC schemes require all the relays to overhear the signal transmitted from all the sources in the network and also a large number of time-slots to achieve full diversity in a multipointto-multipoint transmission, which is particularly challenging for large cellular networks. In this paper, we exploit a basic knowledge of the network topology, i.e. the knowledge of the base stations overheard by other base stations and users, to reduce drastically the number of time-slots. Our results show that our scheme is able to increase the spectral efficiency with a marginal decrease of the spatial diversity compared to traditional STNC.

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“…For the sake of simplicity, we focus on the widely-used linear Wyner model [9] to formulate the considered system as shown in Fig. 1.…”

Section: System Modelmentioning

confidence: 99%

Topology-aware space-time network coding

Torrea-Duran

Morales-Céspedes

Plata-Chaves

et al. 2017

2017 25th European Signal Processing Conference (EUSIPCO)

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“…We modify the widely studied planar Wyner network [2,[28][29][30][31][32] to a three-cell clustered cooperative network. In [28], a two-dimensional hexagonal array of cells is considered, as shown in Fig.…”

Section: Modified Planar Wyner Modelmentioning

confidence: 99%

Mitigating inter-cluster interference on the uplink for a three-cell clustered cooperative network

Thampi

Armour

Fan

et al. 2016

J Wireless Com Network

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In this paper, we propose a practical and scalable solution to mitigating interference on the uplink through static clustering and adaptive fractional frequency reuse (CFFR). The focus is on a three-cell clustered network due to its low complexity. Moreover, we have previously shown that a performance comparable to that of global coordination is achievable using a cluster size of three. In this paper, for a clustered planar Wyner network, we derive analytical capacity equations for zero forcing (ZF) and linear minimum mean squared error (LMMSE)-based receivers. The theoretical results show that inter-cluster interference is the major performance bottleneck and that the smallest interference from the neighbouring clusters is sufficient to significantly lower the system performance. We then switch our study to a more realistic network setting and augment our CFFR technique by adopting an entirely distributed architecture and by implementing a location classification algorithm based on logistic regression. We then show through simulations that CFFR performs significantly better than the widely studied dynamic clustering (DC) technique. Since the inter-cluster interference intensity of CFFR is much lower than DC, the per-cell sum rate performance is 1.5× better, especially at high loads. We also show that the CFFR algorithm is a lot less complex than DC in terms of running time.

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“…The CSI requirements were reduced in [191,114,246] by using the so-called Wyner model from [299] where interference only comes from immediate neighboring cells; see Example 1.1 for details. This enables relatively simple analysis, but the results can also be oversimplified [300]. Another approach is to divide base stations into static disjoint cooperation clusters as in Figure 1.4 [106,174,323].…”

Section: Extending Single-cell Downlink To Multi-cell Downlinkmentioning

confidence: 99%