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تسجيل مستخدم جديدAdaptive Bit Allocation for OFDM Cognitive Radio Systems with Imperfect Channel Estimation
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Cognitive radios hold tremendous promise for increasing the spectral efficiency of wireless communication systems. In this paper, an adaptive bit allocation algorithm is presented for orthogonal frequency division multiplexing (OFDM) CR systems operating in a frequency selective fading environment. The algorithm maximizes the CR system throughput in the presence of narrowband interference, while guaranteeing a BER below a predefined threshold. The effect of imperfect channel estimation on the algorithms performance is also studied.
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In communication systems, efficient use of the spectrum is an indispensable concern. Recently the use of compressed sensing for the purpose of estimating Orthogonal Frequency Division Multiplexing (OFDM) sparse multipath channels has been proposed to
decrease the transmitted overhead in form of the pilot subcarriers which are essential for channel estimation. In this paper, we investigate the problem of deterministic pilot allocation in OFDM systems. The method is based on minimizing the coherence of the submatrix of the unitary Discrete Fourier Transform (DFT) matrix associated with the pilot subcarriers. Unlike the usual case of equidistant pilot subcarriers, we show that non-uniform patterns based on cyclic difference sets are optimal. In cases where there are no difference sets, we perform a greedy search method for finding a suboptimal solution. We also investigate the performance of the recovery methods such as Orthogonal Matching Pursuit (OMP) and Iterative Method with Adaptive Thresholding (IMAT) for estimation of the channel taps.
Coexistence by means of shared access is a cognitive radio application. The secondary user models the slotted primary users channel access as a Markov process. The model parameters, i.e, the state transition probabilities (alpha,beta) help secondary
user to determine the channel occupancy, thereby enables secondary user to rank the primary user channels. These parameters are unknown and need to be estimated by secondary users for each channel. To do so, the secondary users have to sense all the primary user channels in every time slot, which is unrealistic for a large and sparsely allocated primary user spectrum. With no other choice left, the secondary user has to sense a channel at random time intervals and estimate the parametric information for all the channels using the observed slots.
This paper has been withdrawn by the author due to some errors.
Understanding the performance of cognitive radio systems is of great interest. To perform dynamic spectrum access, different paradigms are conceptualized in the literature. Of these, Underlay System (US) has caught much attention in the recent past.
According to US, a power control mechanism is employed at the Secondary Transmitter (ST) to constrain the interference at the Primary Receiver (PR) below a certain threshold. However, it requires the knowledge of channel towards PR at the ST. This knowledge can be obtained by estimating the received power, assuming a beacon or a pilot channel transmission by the PR. This estimation is never perfect, hence the induced error may distort the true performance of the US. Motivated by this fact, we propose a novel model that captures the effect of channel estimation errors on the performance of the system. More specifically, we characterize the performance of the US in terms of the estimation-throughput tradeoff. Furthermore, we determine the maximum achievable throughput for the secondary link. Based on numerical analysis, it is shown that the conventional model overestimates the performance of the US.
This paper has been withdrawn.
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