ترغب بنشر مسار تعليمي؟ اضغط هنا

Simplicial Homology for Future Cellular Networks

189   0   0.0 ( 0 )
 نشر من قبل Anais Vergne
 تاريخ النشر 2013
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English
 تأليف Anais Vergne




اسأل ChatGPT حول البحث

Simplicial homology is a tool that provides a mathematical way to compute the connectivity and the coverage of a cellular network without any node location information. In this article, we use simplicial homology in order to not only compute the topology of a cellular network, but also to discover the clusters of nodes still with no location information. We propose three algorithms for the management of future cellular networks. The first one is a frequency auto-planning algorithm for the self-configuration of future cellular networks. It aims at minimizing the number of planned frequencies while maximizing the usage of each one. Then, our energy conservation algorithm falls into the self-optimization feature of future cellular networks. It optimizes the energy consumption of the cellular network during off-peak hours while taking into account both coverage and user traffic. Finally, we present and discuss the performance of a disaster recovery algorithm using determinantal point processes to patch coverage holes.



قيم البحث

اقرأ أيضاً

With the emergence of Internet-of-Things (IoT) and ever-increasing demand for the newly connected devices, there is a need for more effective storage and processing paradigms to cope with the data generated from these devices. In this study, we have discussed different paradigms for data processing and storage including Cloud, Fog, and Edge computing models and their suitability in integrating with the IoT. Moreover, a detailed discussion on low latency and massive connectivity requirements of future cellular networks in accordance with machine-type communication (MTC) is also presented. Furthermore, the need to bring IoT devices to Internet connectivity and a standardized protocol stack to regulate the data transmission between these devices is also addressed while keeping in view the resource constraint nature of IoT devices.
157 - Sarabjot Singh 2019
Wireless traffic attributable to machine learning (ML) inference workloads is increasing with the proliferation of applications and smart wireless devices leveraging ML inference. Owing to limited compute capabilities at these edge devices, achieving high inference accuracy often requires coordination with a remote compute node or cloud over the wireless cellular network. The accuracy of this distributed inference is, thus, impacted by the communication rate and reliability offered by the cellular network. In this paper, an analytical framework is proposed to characterize inference accuracy as a function of cellular network design. Using the developed framework, it is shown that cellular network should be provisioned with a minimum density of access points (APs) to guarantee a target inference accuracy, and the inference accuracy achievable at asymptotically high AP density is limited by the air-interface bandwidth. Furthermore, the minimum accuracy required of edge inference to deliver a target inference accuracy is shown to be inversely proportional to the density of APs and the bandwidth.
With the seamless coverage of wireless cellular networks in modern society, it is interesting to consider the shape of wireless cellular coverage. Is the shape a regular hexagon, an irregular polygon, or another complex geometrical shape? Based on fr actal theory, the statistical characteristic of the wireless cellular coverage boundary is determined by the measured wireless cellular data collected from Shanghai, China. The measured results indicate that the wireless cellular coverage boundary presents an extremely irregular geometrical shape, which is also called a statistical fractal shape. Moreover, the statistical fractal characteristics of the wireless cellular coverage boundary have been validated by values of the Hurst parameter estimated in angular scales. The statistical fractal characteristics of the wireless cellular coverage boundary can be used to evaluate and design the handoff scheme of mobile user terminals in wireless cellular networks.
In this paper, we propose a transceiver architecture for full-duplex (FD) eNodeB (eNB) and FD user equipment (UE) transceiver. For FD communication,.i.e., simultaneous in-band uplink and downlink operation, same subcarriers can be allocated to UE in both uplink and downlink. Hence, contrary to traditional LTE, we propose using single-carrier frequency division multiple accesses (SC-FDMA) for downlink along with the conventional method of using it for uplink. The use of multiple antennas at eNB and singular value decomposition (SVD) in the downlink allows multiple users (MU) to operate on the same set of ubcarriers. In the uplink, successive interference cancellation with optimal ordering (SSIC-OO) algorithm is used to decouple signals of UEs operating in the same set of subcarriers. A smart antenna approach is adopted which prevents interference, in downlink of a UE, from uplink signals of other UEs sharing same subcarriers. The approach includes using multiple antennas at UEs to form directed beams towards eNode and nulls towards other UEs. The proposed architecture results in significant improvement of the overall spectrum efficiency per cell of the cellular network.
LA planning in cellular network is useful for minimizing location management cost in GSM network. In fact, size of LA can be optimized to create a balance between the LA update rate and expected paging rate within LA. To get optimal result for LA pla nning in cellular network simulated annealing algorithm is used. Simulated annealing give optimal results in acceptable run-time.
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا