Robustness maximization of parallel multichannel systems

Bit error rate (BER) minimization and SNR-gap maximization, two robustness optimization problems, are solved, under average power and bit-rate constraints, according to the waterfilling policy. Under peak-power constraint the solutions differ and this paper gives bit-loading solutions of both robustness optimization problems over independent parallel channels. The study is based on analytical approach with generalized Lagrangian relaxation tool and on greedy-type algorithm approach. Tight BER expressions are used for square and rectangular quadrature amplitude modulations. Integer bit solution of analytical continuous bit-rates is performed with a new generalized secant method. The asymptotic convergence of both robustness optimizations is proved for both analytical and algorithmic approaches. We also prove that, in conventional margin maximization problem, the equivalence between SNR-gap maximization and power minimization does not hold with peak-power limitation. Based on a defined dissimilarity measure, bit-loading solutions are compared over power line communication channel for multicarrier systems. Simulation results confirm the asymptotic convergence of both allocation policies. In non asymptotic regime the allocation policies can be interchanged depending on the robustness measure and the operating point of the communication system. The low computational effort of the suboptimal solution based on analytical approach leads to a good trade-off between performance and complexity.Comment: 27 pages, 8 figures, submitted to IEEE Trans. Inform. Theor

Symbol-Level Multiuser MISO Precoding for Multi-level Adaptive Modulation

Symbol-level precoding is a new paradigm for multiuser downlink systems which aims at creating constructive interference among the transmitted data streams. This can be enabled by designing the precoded signal of the multiantenna transmitter on a symbol level, taking into account both channel state information and data symbols. Previous literature has studied this paradigm for MPSK modulations by addressing various performance metrics, such as power minimization and maximization of the minimum rate. In this paper, we extend this to generic multi-level modulations i.e. MQAM and APSK by establishing connection to PHY layer multicasting with phase constraints. Furthermore, we address adaptive modulation schemes which are crucial in enabling the throughput scaling of symbol-level precoded systems. In this direction, we design signal processing algorithms for minimizing the required power under per-user SINR or goodput constraints. Extensive numerical results show that the proposed algorithm provides considerable power and energy efficiency gains, while adapting the employed modulation scheme to match the requested data rate

Optimizing the joint transmit and receive MMSE design using mode selection

International audienceTo approach the potential multiple-input multiple-output (MIMO) capacity while optimizing the system bit-error rate (BER) performance, the joint transmit and receive minimum mean squared error (joint Tx/Rx MMSE) design has been proposed. It is the optimal linear scheme for spatial multiplexing MIMO systems, assuming a fixed number of spatial streams p as well as fixed modulation and coding across these spatial streams. However, the number of spatial streams has been arbitrarily chosen and fixed, which may lead to an inefficient power allocation strategy and a poor BER performance. In this paper, we relax the constraint of fixed number of streams p and optimize this value for the current channel realization, under the constraints of fixed average total transmit power P/sub T/ and fixed rate R, what we refer to as mode selection . Based on the observation of the existence of a dominant optimal number of streams value for the considered Rayleigh flat-fading MIMO channel model, we further propose an "average" mode selection that avoids the per-channel adaptation through using the latter dominant value for all channel realizations. Finally, we exhibit the significant BER improvement provided by our mode selection over the conventional joint Tx/Rx MMSE design. Such significant improvement is due to the better exploitation of the MIMO spatial diversity and the more efficient power allocation enabled by our mode selection

Multicast Multigroup Precoding and User Scheduling for Frame-Based Satellite Communications

The present work focuses on the forward link of a broadband multibeam satellite system that aggressively reuses the user link frequency resources. Two fundamental practical challenges, namely the need to frame multiple users per transmission and the per-antenna transmit power limitations, are addressed. To this end, the so-called frame-based precoding problem is optimally solved using the principles of physical layer multicasting to multiple co-channel groups under per-antenna constraints. In this context, a novel optimization problem that aims at maximizing the system sum rate under individual power constraints is proposed. Added to that, the formulation is further extended to include availability constraints. As a result, the high gains of the sum rate optimal design are traded off to satisfy the stringent availability requirements of satellite systems. Moreover, the throughput maximization with a granular spectral efficiency versus SINR function, is formulated and solved. Finally, a multicast-aware user scheduling policy, based on the channel state information, is developed. Thus, substantial multiuser diversity gains are gleaned. Numerical results over a realistic simulation environment exhibit as much as 30% gains over conventional systems, even for 7 users per frame, without modifying the framing structure of legacy communication standards.Comment: Accepted for publication to the IEEE Transactions on Wireless Communications, 201

Enhancing Physical Layer Security in AF Relay Assisted Multi-Carrier Wireless Transmission

In this paper, we study the physical layer security (PLS) problem in the dual hop orthogonal frequency division multiplexing (OFDM) based wireless communication system. First, we consider a single user single relay system and study a joint power optimization problem at the source and relay subject to individual power constraint at the two nodes. The aim is to maximize the end to end secrecy rate with optimal power allocation over different sub-carriers. Later, we consider a more general multi-user multi-relay scenario. Under high SNR approximation for end to end secrecy rate, an optimization problem is formulated to jointly optimize power allocation at the BS, the relay selection, sub-carrier assignment to users and the power loading at each of the relaying node. The target is to maximize the overall security of the system subject to independent power budget limits at each transmitting node and the OFDMA based exclusive sub-carrier allocation constraints. A joint optimization solution is obtained through duality theory. Dual decomposition allows to exploit convex optimization techniques to find the power loading at the source and relay nodes. Further, an optimization for power loading at relaying nodes along with relay selection and sub carrier assignment for the fixed power allocation at the BS is also studied. Lastly, a sub-optimal scheme that explores joint power allocation at all transmitting nodes for the fixed subcarrier allocation and relay assignment is investigated. Finally, simulation results are presented to validate the performance of the proposed schemes.Comment: 10 pages, 7 figures, accepted in Transactions on Emerging Telecommunications Technologies (ETT), formerly known as European Transactions on Telecommunications (ETT

Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm

Resource allocation (RA) techniques should be made efficient and optimized in order to enhance the QoS (power & bit, capacity, scalability) of high-speed networking data applications. This research attempts to further increase the efficiency towards near-optimal performance. RA’s problem involves assignment of subcarriers, power and bit amounts for each user efficiently. Several studies conducted by the Federal Communication Commission have proven that conventional RA approaches are becoming insufficient for rapid demand in networking resulted in spectrum underutilization, low capacity and convergence, also low performance of bit error rate, delay of channel feedback, weak scalability as well as computational complexity make real-time solutions intractable. Mainly due to sophisticated, restrictive constraints, multi-objectives, unfairness, channel noise, also unrealistic when assume perfect channel state is available. The main goal of this work is to develop a conceptual framework and mathematical model for resource allocation using Shuffled Frog-Leap Algorithm (SFLA). Thus, a modified SFLA is introduced and integrated in Orthogonal Frequency Division Multiplexing (OFDM) system. Then SFLA generated random population of solutions (power, bit), the fitness of each solution is calculated and improved for each subcarrier and user. The solution is numerically validated and verified by simulation-based powerline channel. The system performance was compared to similar research works in terms of the system’s capacity, scalability, allocated rate/power, and convergence. The resources allocated are constantly optimized and the capacity obtained is constantly higher as compared to Root-finding, Linear, and Hybrid evolutionary algorithms. The proposed algorithm managed to offer fastest convergence given that the number of iterations required to get to the 0.001% error of the global optimum is 75 compared to 92 in the conventional techniques. Finally, joint allocation models for selection of optima resource values are introduced; adaptive power and bit allocators in OFDM system-based Powerline and using modified SFLA-based TLBO and PSO are propose