In this paper, we investigate a joint scheduling and power control for a multi-cell cognitive radio network (CRN) in coexistence with a cellular primary radio network (PRN). The PRN uses a set of licensed orthogonal channels for transmission. This set of channels is also accessed in an opportunistic manner by a set of cognitive radio base stations (CR-BSs) to support secondary users (SUs). The problem is formulated to maximize the spectrum utilization of SUs without causing excessive interference to active primary users (PUs) of the PRN. In addition, all the served SUs must meet a certain QoS. A centralized solution for joint scheduling and power control is derived to give the global accessing decision for all unserved SUs. With the assumption that the knowledge of all subscribers is available, the coordinator of the CRN can use the joint scheduling and power control algorithm to maximize the spectrum utilization of served SUs by solving a mixed-integer linear programming (MILP) with an NP-hard complexity. To avoid the NP-hard complexity, we propose a sub-optimal heuristic algorithm that can be obtained at a much lower complexity based on the coloring interference graph among unserved SUs effected by served SUs and active PUs. Simulation results show that the proposed algorithm can yield the performance close to the optimal solution's.

In this paper, we investigate a joint scheduling and power control for an infrastructure-based cognitive radio network (CRN) in coexistence with a cellular primary radio network (PRN). The PRN uses a set of licensed nonoverlapping orthogonal frequency channels for transmission. This set of channels is also accessed in an opportunistic manner by a set of cognitive radio base stations (CR-BSs) to support secondary users (SUs). The problem is formulated to maximize the spectrum utilization of SUs without causing excessive interference to active primary users (PUs) of the PRN. In addition, all the serviced SUs must meet a certain Quality of Service (QoS), such as satisfying a predefined signal to interference noise ratio (SINR). A centralized solution for joint scheduling and power control is derived to make the global accessing decision for all unserved SUs. With the assumption that the knowledge of all subscribers is available, a coordinator of the CRN can use the joint scheduling and power control algorithm to maximize the spectrum utilization of serviced SUs by solving a mixed-integer linear programming (MILP) with an NP-hard complexity. To avoid the NP-hard complexity, we propose a suboptimal heuristic greedy algorithm that can be obtained at a much lower complexity based on the coloring interference graph among unserved SUs effected by serviced SUs and active PUs. Its superior performance over the existing algorithms is demonstrated through simulations.

In this paper, we propose dynamic spectrum sharing methods for femto base stations (BSs) operated within a macro BS's spectrum area. As the spectrum sharing methods, we provide traffic pattern based resource hopping schemes of the femto BSs. Traffic pattern information which reflects channel activities for each subband used by the macro BS is utilized by the femto BSs to select proper resources. We evaluate our proposed method compared with pure random hopping method in terms of resource hit probabilities. Also we evaluate our proposed method combined with direct interference measurement results, compared with pure interference measurement based random hopping method. Since traffic pattern information reflects future channel activities, simulation results show that the proposed methods can outperform pure random hopping and conventional methods which utilize past information such as interference measurement results only.

In this paper, we investigate a joint scheduling and power control for an infrastructure-based cognitive radio network (CRN) in coexistence with a cellular primary radio network (PRN). The PRN uses a set of licensed orthogonal channels for transmission. This set of channels is also accessed in an opportunistic manner by a set of cognitive radio base stations (CR-BSs) to support secondary users (SUs). The problem is formulated to maximize the spectrum utilization of SUs without causing excessive interference to active primary users (PUs) of the PRN. In addition, all the served SUs must meet a certain QoS. A centralized solution for joint scheduling and power control is derived to give the global accessing decision for all unserved SUs. With the assumption that the knowledge of all subscribers is available, the coordinator of the CRN can use the joint scheduling and power control algorithm to maximize the spectrum utilization of served SUs by solving a mixed-integer linear programming (MILP) with an NP-hard complexity. To avoid the NP-hard complexity, we propose a sub-optimal heuristic greedy algorithm that can be obtained at a much lower complexity based on the coloring interference graph among unserved SUs effected by served SUs and active PUs. Its superior performance oveover other related algorithms is demonstrated through simulations.

In S-MAC-based sensor networks, border nodes consume more energy since they follow multiple listen and sleep schedules. Therefore they switch into the listen state frequently and reduce the network lifetime. This paper proposes a simple but powerful algorithm, termed the schedule unifying algorithm (SUA), to minimize energy consumption of border nodes by unifying multiple listen and sleep schedules into a single unified schedule. The simulation results show that SUA incorporated SMAC- based nodes consume less energy, thereby extending the network lifetime approximately 2 times more.

For the next generation wireless communication systems, inter-cell interference (ICI) is the main source of performance degradation in mobile stations, especially, cell-edge mobile stations. This paper presents a novel orthogonal resource allocation algorithm (ORAA) for our proposed system architecture, termed the OFDMA-based cellular wireless system architecture using relays (OCWSAR). By using relays to cover the cell-edge areas and a robust algorithm with priority resource allocation, the ICI of the system is significantly reduced, while the sector frequency reuse factor is maintained at 1. A system-level simulator is developed in a multi-cell/multi-user environment, where the effect of the proposed ORAA can be evaluated precisely in the presence of inter-cell interference (ICI). Furthermore, the simulation results assure that the new system architecture with the associated algorithm yield higher SINR and data throughput for cell-edge users.

In this paper, we propose an improved orthogonal resource allocation algorithm (iORAA), which is designed to incorporate with the OFDMA-based cellular wireless system architecture using relays (OCWSAR) in order to reduce the inter-cell interference (ICI) significantly for mobile stations (MSs), especially, cell-edge MSs while maintaining the sector frequency reuse factor at 1. Thanks to that, the cell data throughput is also improved. The performance of the proposed algorithm is evaluated in a multicell/multi-user environment, where the effect of the iORAA can be evaluated precisely in the presence of ICI. Numerical results show that the new system with the associated algorithm yield high SINR distribution and data throughput for cell-edge MSs over the conventional algorithms.

In this paper, we introduce a new scheme to improve the performance of the terrestrial-digital multimedia broadcasting (T-DMB) system, which exploits the properties of the Reed-Solomon (RS) decoder to correct more errors by predicting as many erasures as possible in each RS packet in advance before decoding in the RS decoder. The concept depth of prediction (DoP) used for predicting erasures is introduced and derived. Simulation results show that with optimal DoP values, the new scheme yields performance gain of around 1dB at BER of 10-8resulting in the extended coverage area of the T-DMB system.