The performance of long term evolution-advance (LTE-A) depends on different factors such as spectral efficiency, throughput and signal interference to noise ratio (SINR). Interference causes the performance of a network to be grassed to very low level, it directly affects the parameters such as noise interference, receiving diversity and system receiving gain so to mitigate the interference in LTE-A network is very important. Interference occurs in two forms, intra-cell interference and inter-cell interference. Intra-cell interference is removed by orthogonal frequency division multiple access, but the problem of inter-cell interference still exists due to reception of signals from two adjacent base stations at same frequency on user equipment, so coordination is applied between the cells to reduce the interference between the cells. This paper focuses on coordination between the base stations using dynamic cooperative Base Station selection (DCBS). In this paper, SINR, system capacity, minimum and maximum rates of the system are analyzed when coordination is applied between the cells. Three different scenarios are discussed in this paper, which includes coordinated multipoint transmission and reception (COMP), non-COMP and DCBS and then the results of these scenarios are compared.

Comparative Analysis of Intercell Interference Mitigation Techniques in LTE-A Network

Enhancing firefly algorithm with sliding window for continuous optimization problems

Femtocells are the feasible solutions to extend the network coverage of indoor users and to enhance the network capacity in long-term evolution advanced (LTE-A)-based 5G networks. However, the femtocell base station shares the same frequency spectrum of microcell base station in unplanned manner. Hence, interference mitigation is a crucial problem in densely deployed femtocell environment and it is more severe with the deployment of femtocells in LTE-A network. In this paper, a modified dirty paper coding is proposed for interference mitigation along with the optimization of feedback bits using natural inspired meta-heuristic firefly algorithm. The proposed meta-heuristic algorithm reduces the interference by periodically unicasting the channel state information. Since the bandwidth of feedback system is limited, it is optimized in such a way that it does not affect the performance of the system. As compared to the conventional zero-forcing pre-coding, the proposed modified dirty paper coding along with firefly algorithm scheme offers improved sum rate of 70% and 64% with increase in the number of feedback bits and number of users, respectively.

Optimization of feedback bits using firefly algorithm for interference reduction in LTE femtocell networks

The major challenge in Long Term Evolution Advanced (LTE-A) based 5G network is to improve the cell capacity and cell coverage of indoor users. To fulfill these demands, low power Femto Base stations are deployed at homes and company premises. Such heterogeneous network introduces interference due to both Femtocell and microcell users, especially for cell edge users as the frequencies are reused intrusively. In this Paper, we are introduce a modified dirty paper coding technique to mitigate the effect of inter-cell interference. To reduce the effect of interference, each user feedback quantize CSI to base station and then appropriate precoding is done on transmitted signal. Here, we are compare the sum rate of the Modified Dirty Paper Coding and Zero-Forcing technique. Simulation results shows that sum rate of Modified dirty paper coding is 23% more than Zero-Forcing technique.

Kartiki Chikte

Papers

Performance analysis of an improved CSI feedback technique for LTE-A system with Femtocell Interference

Optimization of feedback bits using firefly algorithm for interference reduction in LTE femtocell networks