Wonsop Kim

Optimization of multi-cluster multi-group based cooperative sensing in cognitive radio networks

In cognitive radio (CR) networks, there are two parameters associated with spectrum sensing: probability of detection (PoD) and probability of false alarm (PoF). The higher the PoD, the better the primary users (PUs) are protected. On the other hand, the lower the PoF, the more the throughput of secondary users (SUs) can be achieved. When the cooperative spectrum sensing is used, the performance of these two parameters depends heavily on the fusion scheme. In this paper, the multi-cluster multi-group based cooperative spectrum sensing scheme is proposed. By using k-out-of-N fusion rule, we obtain the optimal number of groups which minimizes the error rate of a cluster. Computer simulations show that the significant improvement of the total error rate in CR networks can be achieved when optimized parameters from the k-out-of-N fusion rule are used.

Distribution of Eigenvalues for 2x2 MIMO Channel Capacity Based on Indoor Measurements

Based on the non line-of-sight (NLOS) indoor measurements performed in the corridors on the third floor of the Electronics and Telecommunications Research Institute (ETRI) building in Daejeon city, Republic of Korea, we investigated the distribution of the eigenvalues of HH*, where H denotes a 2×2 multiple-input multiple-output (MIMO) channel matrix. Using the observation that the distribution of the measured eigenvalues matches well with the Gamma distribution, we propose a model of eigenvalues as Gamma distributed random variables that prominently feature both transmitting and receiving correlations. Using the model with positive integer k_i, i=1, 2, which is the shape parameter of a Gamma distribution, we derive the closed-form ergodic capacity of the 2×2 MIMO channel. Validation results show that the proposed model enables the evaluation of the outage and ergodic capacities of the correlated 2×2 MIMO channel in the NLOS indoor corridor environment.

Dynamic Spectrum Allocation with Efficient SINR-Based Interference Management

This paper considers a dynamic spectrum allocation (DSA) model that a spectrum broker (SB) coordinates the allocation of the spectrum with the regional license inside the region of responsibility. It has a potential to leverage the spectrum utilization but requires a sophisticated approach to manage the allocation-dependent interference effect. Thus, the SB is responsible to manage the wireless interference between base stations (BSs) within the region for quality of service (QoS) provisioning over the allocated channels. In this paper, we address the interference constrained DSA problem and propose an interference management scheme that collaboratively works with the spectrum allocation algorithm to implement the DSA. By the allocation-aware interference management based on the received signal-to-interference-plus-noise-ratio (SINR), the proposed scheme can reflect the context of the SBs decisions at the allocation process. Simulation results demonstrate that the proposed scheme efficiently distributes the spectrum resource while guaranteeing the QoS requirements of all BSs with allocated channels.

Joint power and admission control for underlay spectrum sharing in cognitive radio networks

Underlay spectrum sharing in cognitive radio (CR) networks allows that the secondary user (SU) coexists with the primary user (PU) via primary spectrum sharing to the extent not to deteriorate the primary communication. It provides the SU with more access opportunity than the overlay one, but involves the risk that the quality of service (QoS) of the PU is degraded. In this context, controlling the transmit power of the SU can contribute to guarantee the QoS requirement of the PU and satisfy the QoS requirement for the SUs opportunistic communication to be reliable. However, finding an optimal set which maximizes the number of SUs satisfying both QoS requirements of the SU and the PU is a NP-complete problem. In this paper, we propose a joint power and admission control (JPAC) algorithm for CR networks which achieves a near-optimal performance without exhaustive search. The admission control algorithm removing SUs one-by-one is carried out jointly with the power control algorithm recursively until all remaining SUs satisfy the QoS requirements of the PU and the SU simultaneously. Through the simulation results, we demonstrate that the proposed JPAC algorithm guarantees the QoS requirement of the PU and adjoins the optimal performance with only reasonable force.

Time-Division Multiplexing Based MIMO Channel Sounder Using Loosely Synchronous Codes

In this paper, we propose the time-division multiplexing (TDM) based MIMO channel sounding technique using loosely synchronous (LS) codes for real time measurement of MIMO radio channel. Since LS codes have perfect autocorrelation and cross-correlation functions within certain vicinity of the zero shifts, the proposed technique can substantially reduce multipath channel interference. When cumulative distribution functions (CDFs) of absolute root mean square (RMS) delay spread error are considered, simulation results show that the proposed technique outperforms the conventional TDM based MIMO channel sounding technique. Moreover, in the MIMO channel environment where a mobile station moves with various speeds, the proposed technique is more efficient than the conventional TDM based MIMO channel sounding technique, because the proposed technique obtains about twice the measurement data of the conventional TDM based MIMO channel sounding technique at given time slots.

Performance Analysis of Spatially Correlated MIMO-OFDM Beamforming Systems with the Maximum Eigenvalue Model from Measured MIMO Channels

The performance of MIMO-OFDM beamforming systems with maximal ratio combining receivers is considered based on the extensive wideband 2 × 8 (i.e., 2 transmitting and 8 receiving antennas) MIMO channel measurement data in non line-of-sight urban macrocell environments. Using the experimental observation that the probability density function (PDF) of the measured maximum eigenvalue for H† mHm, where Hm and superscript † denote a MIMO channel frequency response matrix and conjugation and transposition, respectively, matches the Gamma distribution well, we propose the maximum eigenvalue model as Gamma distributed random variables whose parameters are both transmitting and receiving correlations and the number of receiving antennas. Using the model, the performances of MIMO-OFDM beamforming systems, such as the PDF of the output signal-to-noise ratio, outage probability, symbol error rate, and achievable diversity order, are analyzed to demonstrate the effect of spatial correlation in the realistic 2 × n (downlink) and n × 2 (uplink) MIMO channels.

An autocorrelation model for shadow fading in rural macro environments

We propose an autocorrelation model of SF (shadow fading) in LOS (line-of-sight) rural macro environments. The proposed model is based on the empirical autocorrelations obtained from wideband MIMO (multiple input multiple output) channel measurements at 2.38 and 3.705 GHz. It was found that the SF depends on frequency and so do the empirical autocorrelations. The proposed model provides good matches to empirical autocorrelations in the individual measurement routes.

Distribution of eigenvalues for 2×N MIMO channel capacity based on urban microcell measurements

In this paper, we investigate the distribution of eigenvalues of HH† where the H and superscript † denote the MIMO (multiple input multiple output) channel matrix measured in urban microcell and conjugation and transposition. Our channel sounding system is the BECS (band exploration and channel sounding) 2006, which works at a carrier frequency of 3.705 GHz with 100 MHz bandwidth. From the measured data, It is observed that the distribution of eigenvalues of HH† almost fits with Gamma distribution. We derive simple expressions of mean and variance of eigenvalues, which are functions of the absolute values of Tx (transmit) and Rx (receive) antenna correlation coefficients and the number of Rx antennas. Using the expressions of mean and variance, we then model the eigenvalues as Gamma distributed random variables for 2×N (i.e., 2 Tx and N Rx antennas) MIMO channel capacity. Monte Carlo simulations are used to generate eigenvalue realizations according to the model. The results are compared with the measure data and good agreements are found.

SINR Distribution for MIMO MMSE Receivers in Transmit-Correlated Rayleigh Channels: SER Performance and High-SNR Power Allocation

In this paper, a multiple-input-multiple-output (MIMO) system with a precoder is considered in transmit-correlated Rayleigh channels. We specifically target the MIMO system employing minimum-mean-square-error (MMSE) receivers. Based on the random matrix theory, we first present a direct and generalized formulation for deriving a probability density function (pdf) of the signal-to-interference-plus-noise ratio (SINR). Then, we derive accurate closed-form SINR pdfs for a small number of transmit and receive antennas. Based on the SINR pdfs, tight closed-form approximations of the symbol error rate (SER) are derived. In the high-signal-to-noise-ratio (SNR) regime, we also propose high-SNR power allocation (HPA) by minimizing the modified global SER approximation. At high SNRs, the computationally efficient HPA performing similar to optimal power allocation (PA) shows noticeable performance gain over the equal PA, particularly at the high transmit correlation. Moreover, the performance gain of the proposed HPA increases with the diversity order.

Modeling of Eigenvalues for MIMO Channel Capacity Based on Outdoor Measurements

This paper aims at modeling of eigenvalues for 2×N (i.e., 2 transmit and N receive antennas) channel capacity based on non line-of-sight (NLOS) wideband outdoor measurements. Our channel sounding system is the Band Exploration and Channel Sounding System (BECS) 2005, which works at a carrier frequency of 3.7 GHz with 100 MHz bandwidth. From the measured data, we investigate transmit antenna correlation coefficient (TxACC), receive antenna correlation coefficient (RxACC), channel capacity and eigenvalues of HH * where H and (*) are channel frequency response matrix and conjugate transpose. Based on eigenvalue characteristics, we derive mean and variance of eigenvalue which are a function of the absolute value of TxACC, |TxACC|, the absolute value of RxACC, |RxACC|, and the number of Rx antennas, and then model eigenvalues for 2×N channel capacity. Monte Carlo simulations are used to generate eigenvalue realizations according to the model. The results are compared with the measure data and good agreements are found. Keywords-antenna correlation; capacity; CDF; channel sounder;