In this paper, we formulate an optimization problem for secure resource allocation and scheduling in orthogonal frequency division multiple access (OFDMA) half-duplex decode-and-forward (DF) relay assisted networks. Our problem formulation takes into account artificial noise generation to combat a passive multiple antenna eavesdropper and the effects of imperfect channel state information at the transmitter (CSIT) in slow fading. The optimization problem is solved by dual decomposition which results in a highly scalable distributed iterative resource allocation algorithm. The packet data rate, secrecy data rate, power, and subcarrier allocation policies are optimized to maximize the average secrecy outage capacity (bit/s/Hz securely and successfully delivered to the users via relays). Simulation results illustrate that our proposed distributed iterative algorithm converges to the optimal solution in a small number of iterations and guarantees a non-zero secrecy data rate for given target secrecy outage and channel outage probability requirements.

Secure Resource Allocation and Scheduling for OFDMA Decode-and-Forward Relay Networks

Recently, substantial attention has been paid to increase the achievable rates of wireless networks using different kinds of limited channel quality information feedback. Hybrid automatic repeat request (ARQ) and quantized channel state information (CSI) feedback are two well-known approaches applied by experts to provide the limited channel quality information at the transmitter. Considering quasi-static fading channels, this paper aims to provide some comparisons between the performance of these methods from different points of view. The paper first investigates the power- and outage-limited performance of hybrid ARQ and quantized CSI schemes under short- and long-term power constraints. Then, 1) the feedback signaling load, 2) robustness and 3) the complexity of these schemes are compared under short-term transmission power constraint. Both INcremental Redundancy (INR) and Repetition Time Diversity (RTD) approaches are considered for hybrid ARQ feedback. Finally, approximate low-complexity solutions are presented for power allocation in the INR ARQ-based scheme under long-term transmission power constraint. Analytical and numerical results demonstrate the equivalency or the superiority of these approaches in different circumstances.

On Hybrid ARQ and Quantized CSI Feedback Schemes in Quasi-Static Fading Channels

In this paper, we investigate a wireless-powered dual-hop relaying multiple-input multiple-output system, which consists of a multi-antenna source (S) node, a multi-antenna destination (D) node, and $N (N>1)$ single-antenna wireless-powered relaying nodes. At each relay, a power splitting receiver is applied to process the received signal for information decoding and energy harvesting simultaneously, and a decode-and-forward scheme is adopted to forward the processed information. Furthermore, the energy harvester at each relay is assumed to be non-linear with a saturation threshold to limit the power level of the energy. Assuming imperfect channel state information is available both at S and D, outage performance is investigated when S adopts transmit antenna selection in the presence of feedback delay and D performs maximal ratio combining technique to deal with the multiple copies of signals with channel estimation errors. Taking into account a $K$ th best relay selection criterion, which results in the $K$ th best performance in terms of outage probability for the source-relay-destination link, an analytical expression for OP is derived. Monte Carlo simulation results are presented to verify the accuracy of the derived analytical model.

Outage Analysis of Wireless-Powered Relaying MIMO Systems with Non-Linear Energy Harvesters and Imperfect CSI

Antenna selection in multiple-input-multipleoutput (MIMO) systems preserves diversity gain while significantly reducing hardware complexity. However, imperfect channel state information (CSI) affects performance. In this paper, we first analyze the performance of a MIMO system employing antenna selection at the transmitter and maximal ratio combining (MRC) at the receiver in the presence of feedback delay and channel estimation errors. Then, we determine whether channel prediction can compensate for the effect of feedback delay. Outage probability is analyzed as a function of ?, the correlation coefficient between the CSI used at the receiver for decoding (CSIR) and the CSI used at the transmitter for selection (CSIT). Analytical results show that the effect of feedback delay is more significant than the effect of estimation error. In order to overcome the effect of delay, ? should increase with SNR. For a given SNR, the length of the linear minimum mean square error (LMMSE) prediction filter required is calculated and shown to increase with SNR. Finally, we determine the asymptotic diversity order as a function of the feedback quality. Results show that if 1 - ? ? SNR-1, the diversity order with imperfect CSI is same as that with perfect CSI.

/pdf/using-delayed-feedback-for-antenna-selection-in-mimo-systems-317d1rikvd.pdf

Using delayed feedback for antenna selection in MIMO systems

We propose a new optimal location-based beamforming (LBB) scheme for the wiretap channel, where both the main channel and the eavesdropper’s channel are subject to Rician fading. In our LBB scheme, the two key inputs are the location of the legitimate receiver and the location of the potential eavesdropper. Notably, our scheme does not require any channel state information of the main channel or the eavesdropper’s channel being available at the transmitter. This makes our scheme easy to deploy in a host of application settings in which the location inputs are known. Our beamforming solution assumes a multiple-antenna transmitter and a multiple-antenna eavesdropper, and its aim is to maximize the physical layer security of the channel. To obtain our solution, we first derive the secrecy outage probability of the LBB scheme in an easy-to-evaluate expression that is valid for arbitrary real values of the Rician $K$ -factors of the main channel and the eavesdropper’s channel. Using this expression, we then determine the location-based beamformer solution that minimizes the secrecy outage probability. To assess the usefulness of our new scheme, and to quantify the value of the location information to physical layer security, we compare our scheme to other schemes, some of which do not utilize any location information. Our new beamformer solution provides optimal physical layer security for a wide range of location-based applications.

Location-Based Beamforming for Enhancing Secrecy in Rician Wiretap Channels

We investigate the effect of feedback delay on the outage probability of multiple-input single-output (MISO) fading channels. Channel state information at the transmitter (CSIT) is a delayed version of the channel state information available at the receiver (CSIR). We consider two cases of CSIR: (a) perfect CSIR and (b) CSI estimated at the receiver using training symbols. With perfect CSIR, under a short-term power constraint, we determine: (a) the outage probability for beamforming with imperfect CSIT (BF-IC) analytically, and (b) the optimal spatial power allocation (OSPA) scheme that minimizes outage numerically. Results show that, for delayed CSIT, BF-IC is close to optimal for low SNR and uniform spatial power allocation (USPA) is close to optimal at high SNR. Similarly, under a longterm power constraint, we show that BF-IC is better for low SNR and USPA is better at high SNR. With imperfect CSIR, we obtain an upper bound on the outage probability with USPA and BF-IC. Results show that the loss in performance due to imperfection in CSIR is not significant, if the training power is chosen appropriately.

/pdf/outage-probability-of-multiple-input-single-output-miso-13g5edy9f5.pdf

Outage probability of multiple-input single-output (MISO) systems with delayed feedback

Adaptive transmit beamforming based on channel state information (CSI) is a key feature in next generation wireless cellular systems. However, CSI available for adaptation is imperfect due to feedback delay and estimation errors. In this work, we analyze the outage performance of maximum eigen-mode beamforming with imperfect CSI. First we analyze the outage probability in terms of the correlation coefficient ρ between the CSI available at the transmitter (CSIT) and the CSI available at the receiver (CSIR). The analysis shows that feedback delay leads to significant degradation at medium and high signal-to-noise ratios (SNR). Furthermore, the effect of delay can be overcome only if ρ tends to one with increasing SNR. Then, we study whether linear minimum mean squared error (MMSE) prediction can achieve the required behavior in ρ. The length of the prediction filter required is numerically evaluated and shown to increase with SNR. Finally, the asymptotic diversity order is analyzed as a function of the rate at which 1 − ρ approaches 0 as the SNR → ∞. Results show that for 1 − ρ proportional to SNR−1, the asymptotic diversity order remains unaltered.

/pdf/eigen-beamforming-with-delayed-feedback-and-channel-mjgv7j5chx.pdf

Eigen-beamforming with delayed feedback and channel prediction

In this paper, we analyze the performance of an adaptive Multiple Input Multiple Output (MIMO) system employing transmit antenna selection and rate adaptation based on channel state information (CSI). Imperfections in CSI due to estimation error and feedback delay are considered. Since CSI is imperfect, the rate of transmission is chosen in order to meet a target outage probability. The average throughput is evaluated for various cases of imperfect CSI using Monte Carlo simulations. Simulation results show that rate adaptation provides significant gains even with imperfect CSI. Furthermore, prediction can be used to effectively combat the effect of feedback delay.

/pdf/rate-adaptation-in-mimo-antenna-selection-system-with-3pxk7knr60.pdf

Rate adaptation in MIMO antenna selection system with imperfect CSIT

Adaptive transmission schemes based on channel state information at the transmitter have the potential to significantly improve the performance of a wireless system by matching the transmitted signal to the time varying wireless channel conditions. However, channel estimation errors and feedback delay can limit the performance gain. In this paper, the performance gain that can be obtained using channel prediction in an adaptive beamforming system with channel estimation error and feedback delay is evaluated. Channel prediction is shown to improve outage performance significantly by reducing the effect of feedback delay. Results also show that, for a given target outage performance, channel prediction allows the system to operate at much larger channel Doppler spread.

/pdf/on-using-channel-prediction-in-adaptive-beamforming-systems-2ts4s9zn39.pdf

T. R. Ramya

Papers

Using delayed feedback for antenna selection in MIMO systems

Outage probability of multiple-input single-output (MISO) systems with delayed feedback

Eigen-beamforming with delayed feedback and channel prediction

Rate adaptation in MIMO antenna selection system with imperfect CSIT

On Using Channel Prediction in Adaptive Beamforming Systems