Slow Adaptive OFDMA Systems Through Chance Constrained Programming

Adaptive OFDMA has recently been recognized as a promising technique for providing high spectral efficiency in future broadband wireless systems. The research over the last decade on adaptive OFDMA systems has focused on adapting the allocation of radio resources, such as subcarriers and power, to the instantaneous channel conditions of all users. However, such "fast" adaptation requires high computational complexity and excessive signaling overhead. This hinders the deployment of adaptive OFDMA systems worldwide. This paper proposes a slow adaptive OFDMA scheme, in which the subcarrier allocation is updated on a much slower timescale than that of the fluctuation of instantaneous channel conditions. Meanwhile, the data rate requirements of individual users are accommodated on the fast timescale with high probability, thereby meeting the requirements except occasional outage. Such an objective has a natural chance constrained programming formulation, which is known to be intractable. To circumvent this difficulty, we formulate safe tractable constraints for the problem based on recent advances in chance constrained programming. We then develop a polynomial-time algorithm for computing an optimal solution to the reformulated problem. Our results show that the proposed slow adaptation scheme drastically reduces both computational cost and control signaling overhead when compared with the conventional fast adaptive OFDMA. Our work can be viewed as an initial attempt to apply the chance constrained programming methodology to wireless system designs. Given that most wireless systems can tolerate an occasional dip in the quality of service, we hope that the proposed methodology will find further applications in wireless communications

Secure Layered Transmission in Multicast Systems with Wireless Information and Power Transfer

This paper considers downlink multicast transmit beamforming for secure layered transmission systems with wireless simultaneous information and power transfer. We study the power allocation algorithm design for minimizing the total transmit power in the presence of passive eavesdroppers and energy harvesting receivers. The algorithm design is formulated as a non-convex optimization problem. Our problem formulation promotes the dual use of energy signals in providing secure communication and facilitating efficient energy transfer. Besides, we take into account a minimum required power for energy harvesting at the idle receivers and heterogeneous quality of service (QoS) requirements for the multicast video receivers. In light of the intractability of the problem, we reformulate the considered problem by replacing a non-convex probabilistic constraint with a convex deterministic constraint. Then, a semidefinite programming relaxation (SDR) approach is adopted to obtain an upper solution for the reformulated problem. Subsequently, sufficient conditions for the global optimal solution of the reformulated problem are revealed. Furthermore, we propose two suboptimal power allocation schemes based on the upper bound solution. Simulation results demonstrate the excellent performance and significant transmit power savings achieved by the proposed schemes compared to isotropic energy signal generation.Comment: 7 pages, 3 figures, accepted for presentation at the IEEE International Conference on Communications (ICC), Sydney, Australia, 201

Outage-constrained robust power allocation for downlink MC-NOMA with imperfect SIC

In this paper, we study power allocation for downlink multi-carrier non-orthogonal multiple access (MC-NOMA) systems and examine the effects of residual cancellation errors resulting from imperfect successive interference cancellation (SIC) on the system performance. In the presence of random SIC errors, we study outage probability of minimum reserved rate for individual user and formulate outage-constrained robust optimization to minimize the total transmit power. Since the problem is non-convex due to probabilistic constraints, complementary geometric programming (CGP) and arithmetic geometric mean approximation (AGMA) technique are employed to transform it into a convex form. An efficient iterative algorithm with low computational complexity is developed to solve the optimization problem. Simulation results demonstrate the performance of robust MC-NOMA with imperfect SIC and compare that to non-robust MC-NOMA and orthogonal multiple access (OMA) schemes

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Synchronization in wireless communications

The last decade has witnessed an immense increase of wireless communications services in order to keep pace with the ever increasing demand for higher data rates combined with higher mobility. To satisfy this demand for higher data rates, the throughput over the existing transmission media had to be increased. Several techniques were proposed to boost up the data rate: multicarrier systems to combat selective fading, ultra wide band (UWB) communications systems to share the spectrum with other users, MIMO transmissions to increase the capacity of wireless links, iteratively decodable codes (e.g., turbo codes and LDPC codes) to improve the quality of the link, cognitive radios, and so forth