Power optimization, network coding and decision fusion in multi-access relay networks

Multi-access relay (MAR) assisted communication appears in various applications such as hierarchical wireless sensor networks (WSN), two-way relay channels (TWRC) etc. since it provides a high speed and reliable communication with considerably large coverage. In this thesis, we develop the optimal power allocation, network coding and information fusion techniques to improve the performance of MAR channel by considering certain criterion (e.g., minimizing the average symbol error rate (SER) or maximizing the average sum-rate. For this purpose, we first derive optimal information fusion rules for hierarchical WSNs with the use of complete channel state information (CSI) and the partial CSI using channel statistics (CS) with the exact phase information. Later, we investigate the optimization of the MAR channel that employs complex field network coding (CFNC), where we have used two different metrics during the optimization: achievable sum rate and SER bound of the network under the assumption of receiver CSI. After that, we formulate the optimal power allocation problem to maximize the achievable sum rate of the MAR with decode and forward relaying while considering fairness among users in terms of their average achievable information rates under the constraints on the total power and network geometry. We show that this problem is non-convex and nonlinear, and obtain an analytical solution by properly dividing parameter space into four regions. Then, we derive an average SER bound for the CFNC coded MAR channel and aim to jointly optimize the CFNC and the relay power by minimizing SER bound under the total power constraint, which we prove as a convex program that cannot be solved analytically since the Karush-Khun-Tucker (KKT) conditions result in highly nonlinearity equations. Following that, we devise an iterative method to obtain SER optimal solutions which uses the information theoretical rate optimal analytical solution during the initialization and we show that this speeds up the convergence of the iterative method as compared to equal power allocation scheme. Next, we integrate CFNC into WSNs that operate over non-orthogonal communication channel, and derive optimal fusion rule accordingly, combine the SER bound minimization and the average rate-fairness ideas to come up with an approximate analytical method to jointly optimize CFNC and the relay power. Simulation results show that the proposed methods outperform the conventional methods in terms of the detection probability, achievable average sum-rate or average SER

Distributed detection algorithms for parallel and hierarchical wireless sensor networks

Wireless Sensor Networks (WSNs) have recently attracted a lot of attention in various potential applications in military, health, environment and commerce due to their detection, processing and communication capabilities. In this thesis, we consider distributed detection problem for both parallel and hierarchical topology in which sensor decisions are sent over non-ideal wireless channels. We first investigate optimal fusion rules in Neyman-Pearson sense for all considered network configuration. We then, suggest suboptimal fusion rules to decrease computational complexity of the optimal fusion rules. Thirdly, multi-bit distributed detection is investigated both analytically and numerically to increase the detection performance. Finally, we propose fusion center diversity by employing multiple antennas at the fusion center to improve the detection performance of the network and derive optimum fusion rules accordingly. Simulation results suggest that fusion center diversity increases the probability of detection for a given constant false alarm probability

Distributed detection in wireless sensor networks using complex field network coding

The signal transmission and the information fusion in the wireless sensor networks (WSN) are conventionally assumed to operate over orthogonal channels, which becomes bandwidth and throughput inefficient. To remedy this inefficiency and to improve the detection performance simultaneously, in this work, we first propose to use relaying with complex field network coding (CFNC), which operates over non-orthogonal channels. This provides not only the diversity in space but also diversity in time as well. In this method, each sensor is assigned a unique pre-determined signature and this provides robustness against the multi-access interference. Secondly, we derive the optimal likelihood ratio test (LRT) based fusion rule for the proposed system. Thirdly, we devise a way to choose the sensor signatures. Finally, we evaluate the detection performance of the proposed scheme and compare it with the performance of the conventional method. The simulation results show that we can obtain up to a 105% improvement using distributed detection with CFNC rather than employing the conventional method in literature. This suggests that the distributed detection with CFNC is a promising technique that can be used in next generation WSNs

Distributed detection using superposition signalling with fusion center diversity (Üstdüşüm işaretleşmeli tümleştirme merkezi çeşitlemesi ile dağıtık sezim)

In this paper, we propose to use superposition signaling in which all sensors are simultaneously operating and the aggregate of the sensors' signals are acquired by the fusion center to increase communication rate compared to conventional signalling. In addition to superposition signaling, we also propose to employ multiple antennas at the fusion center to improve the data rate of the wireless sensor network further, which will be referred as fusion center diversity (FCD). We derive the optimal likelihood ratio test (LRT) based fusion rule for the superposition signaling with FCD. We finally quantify the detection performance of the optimal fusion rule of the superposition signaling with FCD with respect to the performance of the conventional signaling fusion rule. Simulation results suggest that the superposition signaling with FCD can provide up to 175% detection performance over the existing signaling fusion rule

Rate-optimal fair power allocation in complex field network coded relay communications

In this paper, we consider the complex field network coded relay assisted communication (CFNC-RAC) channel. Although CFNC-RAC is spectrally efficient, its bit error rate performance is degraded by multi-access interference, which can be improved by appropriately allocating the user and relay powers. Since the fairness is an important factor for a practical multi-user communication system, we have proposed a rate-optimal fair power adaptation (ROFPA) technique in this work. The proposed ROFPA policy not only aims to maximize the average achievable sum-rate of CFNC-RAC under the use of the decode and forward relaying but also intends to satisfy the average rate-fairness restriction while taking the total power constraint and the network topology into account. We formulate the ROFPA as a non-convex optimization program and then derive an analytical solution for it. Extensive performance evaluation and numerical simulations validate that ROFPA method can provide significant sum-rate with considerable user fairness when compared to symbol-error-rate optimized (SER-OPT) policy proposed by Eritmen et al. (Wirel Netw, 2015. doi:10.1007/s11276-015-0924-1)

Symbol-error rate optimized complex field network coding for wireless communications

In this paper, the complex field network coding (CFNC) over multi-user relay channel with non-orthogonal communications is studied. In order to improve the performance of CFNC coded relay channel, we propose to optimize the CFNC according to the symbol-error rate (SER) characteristics of the network. To achieve such an optimization, we first derive a bound for the SER of the coded relay channel, which uses maximum-likelihood detection both at the relay and destination node. Then, CFNC optimization is formulated as a convex program, which aims to minimize the SER-bound while considering the constraint on total transmit power and the network geometry. We next derive Karush–Kuhn–Tucker (KKT) conditions of optimal CFNC parameters. Due to the existence of nonlinearity in the simplified KKT conditions, a closed form solution for the optimal parameters is not possible. To overcome this difficulty, we also propose an approximate solution for the optimal CFNC, which utilizes an information theoretical result. After the SER-optimized CFNC parameters are determined, we investigate the average bit error rate (BER) of the network for various parameters. The performed numerical experiments reveal that SER-optimized CFNC could provide a BER improvement up-to 29 % over the conventional CFNC for a two-user relay channel

Improving the performance of wireless sensor networks through optimized complex field network coding

Signal transmission and information fusion in wireless sensor networks (WSNs) are conventionally assumed to operate over orthogonal channels, which makes the network bandwidth and throughput inefficient. To remedy this inefficiency and improve the performance of the WSNs, we consider complex field network-coded (CFNC) relay-assisted communications, which operates over nonorthogonal channels and provides both spatial and temporal diversity. We derive the optimal likelihood ratio test-based fusion rule for the considered system. To provide robustness against the multiaccess interference, each sensor in the CFNC-coded system is assigned to a unique predetermined signature. Hence, the signature selection and the relay power allocation become crucial factors affecting the performance of the WSNs. We also develop an analytical method to jointly adjust the sensor signatures and the relay power utilizing the average symbol error rate bound of the network together with some information theoretical results. Finally, we evaluate the detection performance of the proposed scheme and compare it with that of the conventional method. The simulation results suggest that the proposed signature selection and relay power allocation method in the CFNC-coded relay-assisted WSNs considerably improves the network performance