Wireless networks are susceptible to eavesdropping due to its broadcast nature. Recently, physical layer security has been attracting much attention in wireless networks. The key idea of physical layer security is to exploit the wireless channel physical characteristics, such as fading, noise, and diversity, to secure wireless communications. The fundamental ability of the physical layer to provide security is characterized by secrecy capacity, which is defined as the maximum rate of secret information sent from a transmitter to its desired receiver in the presence of an eavesdropper.
We study the secrecy capacity in MIMO systems. By adding artificially generated jamming signal into the information-bearing signal, the eavesdropper's channel can be significantly degraded, but the main channel remains unaffected.
We study the secrecy capacity in MIMO systems. By adding artificially generated jamming signal into the information-bearing signal, the eavesdropper's channel can be significantly degraded, but the main channel remains unaffected.
Precoded multiple-input multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) systems have been considered as one of the candidates for the physical-layer techniques of the next-generation wireless communication systems. Linear precoding requires the channel state information (CSI) at the transmitter to adapt the transmitted signal to the channel conditions. However, the error performance of a precoded system is significantly degraded by feedback delay that causes the CSI outdated at the transmitter.
We proposed a novel multi-block linear channel predictor to cope with the feedback delay in a limited feedback precoded spatial multiplexing MIMO-OFDM system. The time-varying channel is modeled by autoregressive (AR) model, whose coefficients are obtained using linear minimum mean square error (MMSE) algorithm. Channel state information several milliseconds ahead can be accurately predicted by using an iterative method.
We proposed a novel multi-block linear channel predictor to cope with the feedback delay in a limited feedback precoded spatial multiplexing MIMO-OFDM system. The time-varying channel is modeled by autoregressive (AR) model, whose coefficients are obtained using linear minimum mean square error (MMSE) algorithm. Channel state information several milliseconds ahead can be accurately predicted by using an iterative method.
Although OFDM presents numerous advantages, it suffers from performance degradations due to the hardware component flaws in the analog front-ends of the transceivers. The imbalance between the in-phase and the quadrature-phase (I/Q) branches is a key factor in performance degradation. The I/Q imbranches may introduces intercarrier interference (ICI) and frequency-dependent distortion to the received data. Therefore, estimation and equalization of the I/Q imbalances from the received data are critical in OFDM-based systems.
We analyze I/Q imbalances in MIMO-OFDM wireless communication systems over multipath fading channels. A new concept, virtual channel, is introduced to estimate and compensate the joint effect of the fading channel and the I/Q imbalances, resulting in an improved system performance.
We analyze I/Q imbalances in MIMO-OFDM wireless communication systems over multipath fading channels. A new concept, virtual channel, is introduced to estimate and compensate the joint effect of the fading channel and the I/Q imbalances, resulting in an improved system performance.
Self-encoded spread spectrum (SESS) and multiple access communications have been proposed and investigated in many aspects. By deriving its spreading sequences from the user data stream, SESS provides a feasible implementation of random-coded spread spectrum and potentially enhances the transmission security.
We study the performance of SESS in a MIMO system. Using Alamouti scheme, the spread chips can be transmitted via a MIMO channel to take advantage of spatial diversity. The system throughput can be increased by employing multi-codes.
We study the performance of SESS in a MIMO system. Using Alamouti scheme, the spread chips can be transmitted via a MIMO channel to take advantage of spatial diversity. The system throughput can be increased by employing multi-codes.
A practical MIMO channel model is imperative for system performance evaluations. To facilitate our research, we proposed a outdoor-to-indoor statistical channel model that integrates the 3rd Generation Partnership Project (3GPP) spatial channel model extended (SCME) and a spherical power spectrum model at the mobile station (MS). This model can be used for system-level simulations.