Unlike general routing strategies, network coding (NC) can combine encoding functions with multi-path propagation over a network. This allows network capacity to be achieved to support complex security solutions. Moreover, NC has intrinsic security advantages against passive attacks over traditional routing techniques. However, due to the transmission of the global encoding kernels, the system is fragile to eavesdropping attacks with multiple probes. This paper proposes a generic unicast secure transmission scheme based on random linear network coding (RLNC). Specifically, the intended receiver generates a random matrix upon receiving the request from the source node, and then transmits each row vector of this matrix over a link reversely to the source node. Each intermediate node rearranges all received vectors to form a matrix by row, and then post-multiplies its local encoding kernel by this matrix to obtain a new matrix. Similarly, each row vector of the new matrix is reversely transmitted over a link to the source node. This procedure is performed until we have the source node, where the generalized inverse of the received matrix (or part of it) can be used as its local encoding kernel. Hence, the intended receiver can use the generated matrix (or the corresponding part) to decode the received data packets directly. We also analyze the security to demonstrate that the proposed scheme is at least as secure as other methods against wiretapping attacks. We also evaluate the performance of the proposed scheme to demonstrate its utility.

Wireless communication security can be enhanced by leveraging the characteristics of the physical (PHY) layer, where discriminatory scrambling can be employed at the symbol level to either improve the signal quality of the legitimate receiver or degrade that of the eavesdroppers. However, in the presence of multiple passive eavesdroppers with more antennas than the transmitter, the transmitted signals can still be reliably separated from random disturbances. To mitigate this challenge, we propose a two-dimensional vectorized secure transmission scheme. Unlike existing transmission schemes (where the same data symbol is sent over each antenna with a predesigned complex weight at a time), in the proposed scheme, a sequence of data symbols in a predefined order (named symbol vector) is first pre-superposed through pre-coding with a random complex matrix prior to been sent as a vector in parallel over each transmitting antenna at a time. As a result, physical randomness of the legitimate channel is introduced into the received signals at passive eavesdroppers in the pre-coding procedure. Moreover, to ensure that transmitted data symbols can be recovered in the right order, each symbol vector is sent repeatedly, according to the principle of maximum entropy. To ensure the intended receiver can recover the transmitted symbol vector, the random pre-coding matrices are selected such that a linear constraint imposed by the CSI of the legitimate channel is satisfied. In addition, an extended maximum likelihood (ML) detection method is developed for the desired receiver while the random pre-coding matrices are not required to be transmitted. We then analyze its security based on the signal detection theory to demonstrate that the intended receiver can recover the transmitted symbol vectors while the eavesdroppers are not capable of doing so. We also evaluate the performance of the proposed scheme to demonstrate its effectiveness.

As a recently proposed physical layer security scheme, the two-dimensional transmission scheme prevents eavesdropping, but the bit error rate (BER) of the receiver becomes high. A new coding scheme for Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes to improve the performance of the receiver is proposed and named as dimension reduction coding. This new scheme constructs the base matrix, which is necessary to obtain the parity check matrix of QC-LDPC codes, from the channel coefficient matrix of two-dimensional transmission scheme. Then, by analyzing the relationship between the base matrix and the parity check matrix of QC-LDPC codes, we find out the conditions that the base matrix must satisfy so that the corresponding parity check matrix has no shortest cycle in Tanner graph. Furthermore, a dimension reduction algorithm is presented to modify the base matrix and obtain parity check matrices with good performance. Finally, simulation results are given and validate the feasibility of this method.

Internet of Things (IoT) security becomes of great importance, as IoT is the foundation for many emerging services. To safeguard IoT security, cryptosystems at upper layer relying on sophisticated key management alone can face many challenges due to the massive deployment of resource constrained machine-type communication (MTC) devices. Physical layer (PHY) security can complement and enhance IoT security, by exploiting the characteristics of the bottom layer. In PHY security, channel state information (CSI) estimated through reverse pilot training is essential for the sender to select appropriate beamforming/precoder, which however is also vulnerable to adversaries. An adversary can actively launch pilot contamination attacks to affect the channel estimation and improve its signal reception quality. In this paper, we propose a relay-aided vectorized (RAV) secure transmission scheme, to safeguard the downlink communication in IoT networks under potential pilot contamination attacks. The proposed scheme does not distinguish the pilot sequences sent from an adversary and the receiver; and the sender utilizes what it receives to estimate the CSI for beamforming/precoder design. Then, a set of data symbols are presuperposed using a random complex matrix to form signal vectors to send. Through cooperation with a relay, the signal vectors can be recovered by the intended receiver whereas the adversary or the relay cannot, as proved through security analysis. The simulation results also demonstrate that the bit error rate (BER) of the adversary is 0.5 regardless of its channel quality, indicating perfect secrecy is achieved.

Efficient load balancing algorithm is indispensable to serve more mobile stations in the heterogeneous wireless networks. In this paper, we propose a load balancing algorithm based on the velocity and position of mobile station for heterogeneous multitier wireless networks consisting of macrocell system and microcell system. This algorithm is able to balance load by transferring some mobile stations with longer sojourn time from overloaded cells to overlapping heterogeneous under-loaded cells. In addition, velocity, direction of motion and local position can be used to decrease unnecessary handoffs, and high-speed mobile stations can also connect to microcell system. Simulation results of three models show that blocking probability, dropping probability and overall system utilization using the proposed load balancing algorithm are improved significantly.

Efficient load balancing algorithm is indispensable to serve more mobile stations in the heterogeneous wireless networks. In this paper, we propose a dynamic load balancing algorithm based on sojourn time for heterogeneous multitier wireless networks consisting of macrocell cellular network and microcell cellular network. The sojourn time is calculated by the velocity, direction of motion and position of mobile station. This algorithm is able to balance load by transferring some ongoing calls with longer sojourn time from overloaded cells to overlapping under-loaded heterogeneous cells. The number of transferred ongoing calls per load balancing period is calculated by the new calls arrival rate of overloaded cells and the workload states of overlapping cells. In addition, high-speed mobile stations can hand off from macrocells to microcells and slow mobile stations can hand off from microcells to macrocells, which can decrease the call dropping probability. Simulation results show that call blocking probability, call dropping probability and overall system utilization using our proposed dynamic load balancing algorithm are improved significantly.

In this paper, a novel method is presented to guarantee the predefined quality-of-service (QoS) requests such as handoff-dropping probability by forecasting the next possible number of handoff dropping calls, using auto regressive moving average (ARMA) model, to update threshold through a close-loop control, while increasing the statistical multiplexing gain (the number of users provided service in a wireless/mobile system at a time) in providing acceptable QoS grades for every connections. We have tested our algorithm through simulations on a wide variety of traffic input. Our simulation results suggest that the forecasting-based approach enables us to achieve a higher level of statistical multiplexing gain while still reliably meeting the target handoff-dropping probability.