In adaptive beamforming system adaptive algorithm of digital filter is applied to update the weighting vector of the antenna elements to get antenna gain along the desired direction and attenuation along the jammer. The objective of the paper is to evaluate the threshold gain of the adaptive beam former along the line of sight (LOS) between the transmitter and the receiver (including jammer suppression) to make the single hop link comparable with 2-hop link. The single hop and 2-hop communication systems are compared in context of symbol error rate (SER) under fading condition theoretically and verified by simulation. Finally we evaluate the numerical value of threshold gain of adaptive beamformer of two antenna elements under Rayleigh and Nakagami-m fading conditions. Communications much less than the combined SNR of 2-hop wireless link. This phenomenon attracts the researcher to apply the concept of multi-hop in wireless networks to reduce SER and enhance throughput. The performance analysis of two-hop wireless link in context of BER under fading is discussed in [1] [2] [3] [4]. Usually in rural or suburban area the gain of the relay is kept constant called amplify-and-forward (AF) relaying. In a dense urban area the wireless link is found as time selective channel i.e. SNR of receiver varies with time hence the gain of the relay has to be adjusted with feedback signal like adaptive algorithm of digital filter. The concept of AF and DF relay is found in [5] [6] [7] where the idea of channel state information is included. In [8], authors analyzed performance of AF relay network where relay is affected by interferences under assumption that there is no obstacle between interferences and relay i.e. LOS interferences. The paper derived closed form solution of outage probability with the idea of [9] [10]. To reduce BER of 3G mobile cellular destined for high speed communication needs to overcome small scale fading (Rayleigh fading). In this context selection of best relay is discussed in [11] with MIMO (multiple input multiple output). Actually MIMO is used in wireless link to take the advantage of space diversity at the expense of system cost. Different combination of MIMO (both the hop is MIMO, MISO in first hop and SIMO in second hop, SIMO in first hop and MISO in second hop etc.) is found in recent literature for 2-hop wireless link [11] [12] [13]. The main objective of AAS is to combine the radiation pattern of individual antenna element (with proper weighting factor and phase shift) to produce a combined beam of desired directivity and gain. The detail analysis of AAS is found in [14] [15] [16]. To make the system dynamic, adaptive beam forming algorithm is used to select the appropriate weighting factor of antenna elements. Several applications of AAS for example: Beam Steering and Switching, Conventional Beam Forming, Diversity Combining, Array on Satellites, Dynamic beams, Reduction in Delay Spread and Multipath Fading, Reduction in Co-channel Interference etc. are discussed in [14]. The same author discuss...
One of the features of Long Term Evolution (LTE) is the deployment of femtocells as the underlain cell of a macrocell without any intervention of frequency planning to offload the traffic. In this paper we used Markov chain to derive the expression of blocking probability for both macro and femtocell in terms of traffic parameters of the network. We developed an analytical model to find the expression of probability of forced termination (FT) using combination of mobility model and probability tree considering low dense femtocellular network. Two different trees were designed: a newly originating call which starts its session in a femtocell and that of in a macro cell. The link parameters of small scale fading of wireless network under Multiple Input Multiple Output (MIMO) are combined with the proposed traffic model to get the probability of FT of a real-life network. A new state transition chain was also developed including its solution for LTE traffic of variable bandwidth (BW) and a comparison was made with Erlang's traffic model.
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