Gozde Ozcan

Error Rate Analysis of Cognitive Radio Transmissions with Imperfect Channel Sensing

In this paper, error rate performance of cognitive radio transmissions is studied in the presence of imperfect channel sensing decisions. It is assumed that cognitive users first perform channel sensing, albeit with possible errors. Then, depending on the sensing decisions, they select the transmission energy level and employ MI × MQ rectangular quadrature amplitude modulation (QAM) for data transmission over a fading channel. In this setting, the optimal decision rule is formulated under the assumptions that the receiver is equipped with the sensing decision and perfect knowledge of the channel fading. It is shown that the thresholds for optimal detection at the receiver are the midpoints between the signals under any sensing decision. Subsequently, minimum average error probability expressions for M-ary pulse amplitude modulation (M-PAM) and MI × MQ rectangular QAM transmissions attained with the optimal detector are derived. The effects of imperfect channel sensing decisions on the average symbol error probability are analyzed.

Energy-efficient power adaptation for cognitive radio systems under imperfect channel sensing

In this paper, energy efficient power adaptation is considered in sensing-based spectrum sharing cognitive radio systems in which secondary users first perform channel sensing and then initiate data transmission with two power levels based on the sensing decisions (e.g., idle or busy). It is assumed that spectrum sensing is performed by the cognitive secondary users, albeit with possible errors. In this setting, the optimization problem of maximizing the energy efficiency (EE) subject to peak/average transmission power constraints and average interference constraints is considered. The circuit power is taken into account for total power consumption. By exploiting the quasiconcave property of the EE maximization problem, the original problem is transformed into an equivalent parameterized concave problem and Dinkelbachs method-based iterative power adaptation algorithm is proposed. The impact of sensing performance, peak/average transmit power constraints and average interference constraint on the energy efficiency of cognitive radio systems is analyzed.

Energy-Efficient Power Allocation in Cognitive Radio Systems With Imperfect Spectrum Sensing

This paper studies energy-efficient power allocation schemes for secondary users in sensing-based spectrum sharing cognitive radio systems. It is assumed that secondary users first perform channel sensing possibly with errors and then initiate data transmission with different power levels based on sensing decisions. In this setting, the optimization problem is to maximize energy efficiency (EE) subject to peak/average transmission power constraints and peak/average interference constraints. By exploiting the quasi-concave property of the EE maximization problem, the original problem is transformed into an equivalent parameterized concave problem, and an iterative power allocation algorithm based on Dinkelbachs method is proposed. The optimal power levels are identified in the presence of different levels of channel side information (CSI) regarding the transmission and interference links at the secondary transmitter, namely, perfect CSI of both transmission and interference links, perfect CSI of the transmission link, imperfect CSI of the interference link, imperfect CSI of both links, or only statistical CSI of both links. Through numerical results, the impact of sensing performance, different types of CSI availability, and transmit and interference power constraints on the EE of the secondary users is analyzed.

Energy efficiency of hybrid-ARQ systems under QoS constraints

In this paper, energy efficiency of hybrid automatic repeat request (HARQ) schemes under QoS constraints is studied in the low power regime by characterizing the minimum energy per bit and wideband slope. The energy efficiency is investigated when either an outage constraint is imposed and (the transmission rate is selected accordingly) or the transmission rate is optimized to maximize the throughput. In both cases, it is also assumed that there is a limitation on the number of retransmissions due to deadline constraints. Under these assumptions, closed-form expressions are obtained for the minimum energy per bit and wideband slope for HARQ with chase combining (CC). Through numerical results, the performances of HARQ-CC and HARQ with incremental redundancy (IR) are compared. Moreover, the impact of deadline constraints, outage probability, QoS constraints on the energy efficiency is analyzed.

Energy Efficiency of Hybrid-ARQ Under Statistical Queuing Constraints

In this paper, energy efficiency of hybrid automatic repeat request (HARQ) schemes with statistical queuing constraints is studied for both constant-rate and random Markov arrivals by characterizing the minimum energy per bit and wideband slope. In particular, two queuing models are considered. Specifically, when outage occurs, the transmitter keeps the packet, lowers its priority, and attempts to retransmit it later in the first queue model, while the packet is discarded and removed from the buffer in the second queue model. For both models, energy efficiency is investigated when outage constraints, statistical queuing constraints, and deadline constraints are imposed. The deadline constraint provides a limitation on the number of retransmissions or equivalently the number of HARQ rounds. Under these assumptions, closed-form expressions are obtained for the minimum energy per bit and wideband slope for HARQ with chase combining, and comparisons among different arrival models are made. For instance, it is shown that stricter queuing constraints and more bursty sources degrade the energy efficiency by lowering the wideband slope. In the numerical results, analytical characterizations are verified through simulations. Moreover, the impact of source variations/burstiness, deadline constraints, outage probability, and queuing constraints on the energy efficiency is analyzed.

Optimal power control for underlay cognitive radio systems with arbitrary input distributions

This paper studies optimal power control policies that maximize the achievable rates of underlay cognitive radio systems with arbitrary input distributions under both peak transmit/peak interference power constraints and peak transmit/average interference power constraints for general fading distributions. A low-complexity optimal power control algorithm is proposed. Also, the optimal power control policy in the low-power regime is analyzed. In particular, by considering gamma distributed channel power gains of the interference link between the secondary transmitter and the primary receiver and the transmission link between the secondary transmitter and the secondary receiver, closed-form expressions for the maximum achievable rate attained with the optimal power control strategy in the low-power regime are provided. Through numerical results, the impact of the fading severity of both interference and transmission links and transmit power and interference power constraints on the maximum achievable rate of the cognitive user for different constellations and Gaussian signals are investigated.

Multimedia Transmission Over Cognitive Radio Channels Under Sensing Uncertainty

This paper studies the performance of hierarchical modulation-based multimedia transmission in cognitive radio (CR) systems with imperfect channel sensing results under constraints on both transmit and interference power levels. Unequal error protection (UEP) of data transmission using hierarchical quadrature amplitude modulation (HQAM) is considered in which high priority (HP) data is protected more than low priority (LP) data. In this setting, closed-form bit error rate (BER) expressions for HP data and LP data are derived in Nakagami-m fading channels in the presence of sensing errors. Subsequently, the optimal power control that minimizes weighted sum of average BERs of HP bits and LP bits or its upper bound subject to peak/average transmit power and average interference power constraints is derived and a low-complexity power control algorithm is proposed. Power levels are determined in three different scenarios, depending on the availability of perfect channel side information (CSI) of the transmission and interference links, statistical CSI of both links, or perfect CSI of the transmission link and imperfect CSI of the interference link. The impact of imperfect channel sensing decisions on the error rate performance of cognitive transmissions is also evaluated. In addition, tradeoffs between the number of retransmissions, the severity of fading, and peak signal-to-noise ratio (PSNR) quality are analyzed numerically. Moreover, performance comparisons of multimedia transmission with conventional quadrature amplitude modulation (QAM) and HQAM, and the proposed power control strategies are carried out in terms of the received data quality and number of retransmissions.

Image and video transmission in cognitive radio systems under sensing uncertainty

This paper studies the performance of hierarchical-modulation-based image and video transmission in cognitive radio systems with imperfect channel sensing results under constraints on both transmit and interference power. Data intended for transmission is first compressed via source coding techniques and then divided into two priority classes, namely high priority (HP) data and low priority (LP) data, by taking into consideration the unequal importance of bits in the output codestream. After dividing the compressed data into packets of equal size, turbo coding is applied. Finally, the resulting packets are modulated using hierarchical quadrature amplitude modulation (HQAM). In this setting, closed-form bit error probability expressions for HP data and LP data are derived over Nakagami-m fading channels in the presence of sensing errors. Subsequently, the effects of probabilities of detection and false alarm on error rate performance of cognitive transmissions are evaluated. In addition, tradeoffs between the number of retransmissions and peak signal-to-noise ratio (PSNR) quality are analyzed numerically. Moreover, performance comparisons of multimedia transmission with conventional QAM and hierarchical QAM are carried out in terms of the received data quality and number of retransmissions.

QoS-driven power control for fading channels with arbitrary input distributions.

In this paper, the optimal power control policy that maximizes the effective capacity for arbitrary input distributions in fading channels subject to an average power constraint is studied. A low-complexity power control algorithm is proposed. In addition, energy efficiency is investigated by characterizing both the minimum energy per bit and wideband slope for arbitrary signaling in the low-power regime when channel side information (CSI) is available only at the receiver. With perfect CSI at both the transmitter and receiver, the optimal power adaptation strategy in this regime is also determined. Through numerical results, performance comparison with constant power scheme and optimal power adaptation strategy for different signal constellations and Gaussian signals is given. The impact of QoS constraints, input distributions, and average transmit power level on the proposed power control policy, maximum achievable effective capacity and energy efficiency is analyzed.

Effective Capacity Analysis of Fixed-Gain and Variable-Gain AF Two-Way Relaying

In this paper, effective capacity of a two-way amplify and forward (AF) relay channel, in which two source nodes exchange their signals via a relay node, is analyzed. Depending on the availability of the channel side information (CSI), the relay, which operates in half-duplex mode, has a fixed-gain or variable-gain factor. It is assumed that source nodes are subject to individual statistical quality of service (QoS) constraints in the form of limitations on buffer size. Under these assumptions and constraints, a characterization of the throughput for source nodes is provided by obtaining closed-form expressions for lower bounds on the effective capacity. Performances of two-way fixed- gain and variable-gain AF relaying are compared. The relations between buffer constraints, transmission power, the location of the relay node and effective capacity are also studied.