Spectral Efficiency of Multi-User Adaptive Cognitive Radio Networks

In this correspondence, the comprehensive problem of joint power, rate, and subcarrier allocation have been investigated for enhancing the spectral efficiency of multi-user orthogonal frequency-division multiple access (OFDMA) cognitive radio (CR) networks subject to satisfying total average transmission power and aggregate interference constraints. We propose novel optimal radio resource allocation (RRA) algorithms under different scenarios with deterministic and probabilistic interference violation limits based on a perfect and imperfect availability of cross-link channel state information (CSI). In particular, we propose a probabilistic approach to mitigate the total imposed interference on the primary service under imperfect cross-link CSI. A closed-form mathematical formulation of the cumulative density function (cdf) for the received signal-to-interference-plus-noise ratio (SINR) is formulated to evaluate the resultant average spectral efficiency (ASE). Dual decomposition is utilized to obtain sub-optimal solutions for the non-convex optimization problems. Through simulation results, we investigate the achievable performance and the impact of parameters uncertainty on the overall system performance. Furthermore, we present that the developed RRA algorithms can considerably improve the cognitive performance whilst abide the imposed power constraints. In particular, the performance under imperfect cross-link CSI knowledge for the proposed `probabilistic case' is compared to the conventional scenarios to show the potential gain in employing this scheme

Non-Orthogonal Multiple Access for Hybrid VLC-RF Networks with Imperfect Channel State Information

The present contribution proposes a general framework for the energy efficiency analysis of a hybrid visible light communication (VLC) and Radio Frequency (RF) wireless system, in which both VLC and RF subsystems utilize nonorthogonal multiple access (NOMA) technology. The proposed framework is based on realistic communication scenarios as it takes into account the mobility of users, and assumes imperfect channel-state information (CSI). In this context, tractable closed-form expressions are derived for the corresponding average sum rate of NOMA-VLC and its orthogonal frequency division multiple access (OFDMA)-VLC counterparts. It is shown extensively that incurred CSI errors have a considerable impact on the average energy efficiency of both NOMA-VLC and OFDMAVLC systems and hence, they should not be neglected in practical designs and deployments. Interestingly, we further demonstrate that the average energy efficiency of the hybrid NOMA-VLCRF system outperforms NOMA-VLC system under imperfect CSI. Respective computer simulations corroborate the derived analytic results and interesting theoretical and practical insights are provided, which will be useful in the effective design and deployment of conventional VLC and hybrid VLC-RF systems

Adaptive Power Allocation and Control in Time-Varying Multi-Carrier MIMO Networks

In this paper, we examine the fundamental trade-off between radiated power and achieved throughput in wireless multi-carrier, multiple-input and multiple-output (MIMO) systems that vary with time in an unpredictable fashion (e.g. due to changes in the wireless medium or the users' QoS requirements). Contrary to the static/stationary channel regime, there is no optimal power allocation profile to target (either static or in the mean), so the system's users must adapt to changes in the environment "on the fly", without being able to predict the system's evolution ahead of time. In this dynamic context, we formulate the users' power/throughput trade-off as an online optimization problem and we provide a matrix exponential learning algorithm that leads to no regret - i.e. the proposed transmit policy is asymptotically optimal in hindsight, irrespective of how the system evolves over time. Furthermore, we also examine the robustness of the proposed algorithm under imperfect channel state information (CSI) and we show that it retains its regret minimization properties under very mild conditions on the measurement noise statistics. As a result, users are able to track the evolution of their individually optimum transmit profiles remarkably well, even under rapidly changing network conditions and high uncertainty. Our theoretical analysis is validated by extensive numerical simulations corresponding to a realistic network deployment and providing further insights in the practical implementation aspects of the proposed algorithm.Comment: 25 pages, 4 figure

Energy efficient green wireless communication systems with imperfect CSI and data outage

Modern applications involve green communication technologies motivating well optimisation in the power–limited regime. In comparison to most of existing related work that assumes perfect channel state information (CSI) is always available, which is unfortunately not true in reality, this work focuses on an optimal energy efficient solution for resource allocation in multiuser orthogonal frequency division multiple access (OFDMA) networks in the presence of imperfect CSI and data outage conditions. Particularly, in view that wireless channel conditions, circuit power consumptions and users’ quality–of–service (QoS) requirements are heterogeneous in nature, we enable attractive tuning options by letting energy efficiency optimisation objective to assign weights to each allocation link. Also, we interpret effects of data outage due to imperfect CSI using a profound insight on the monotonicity of noncentral chi-squared inverse distribution function, which reveals that our design complies with expected physics and mechanics of conventional energy efficiency approach and that it can be successfully degenerated to the energy efficiency model with perfect CSI. Furthermore, we formulate a mixed combinatorial problem towards maximising the energy efficiency subject to a minimum QoS requirement, channel interference and transmitting power constraints. The problem is transformed into an equivalent quasiconcave problem with respect to power, and concave problem with respect to the subcarrier indexing coefficients using the concept of subcarrier time–sharing. We optimise through a simple and versatile methodology, which uses standard–Lagrangian optimisation technique to obtain joint dynamic subcarrier and adaptive power allocations by means of final formulas. We also examine key properties of the introduced optimal solution in terms of implementation convergence and complexity, level of optimality, and impact of imperfect CSI coefficients and circuit power on network performance. The simulation results demonstrate the effectiveness of our allocation scheme for achieving higher energy efficiency performance with the guaranteed QoS support and lower complexity than existing approaches especially when perfect CSI is not available