This paper addresses the utility-based radio resource allocation problem in DS-CDMA systems carrying multimedia traffic. The proposed scheme, aiming at achieving optimal resource allocation, considers the joint power and data rate allocation. To avoid high computational complexity of nonlinear optimization, we reformulate the radio resource allocation problem as a market model, where resource is regarded as a commodity. Since the market model satisfies the incentive-compatible constraint, the optimal resource allocation can be obtained at the market equilibrium in a distributed manner. According to whether to allocate a minimal transmission data rate to each user, two algorithms, UCA and FCA, are proposed. UCA emphasize on maximizing system overall utilities, while FCA guarantees fairness to users. Simulation results show that the proposed radio resource allocation scheme and algorithms are flexible and efficient for multimedia DS-CDMA systems.

In wireless communication systems where users compete for limited bandwidth, radio resource control is essential for throughput enhancement and delay reduction. In this paper, we present a game-theoretical approach to distributed resource control in CDMA systems. Incomplete information about channel conditions is considered. The resource control problem is formulated as a noncooperative game of incomplete information, with which the existence and uniqueness of the Bayesian Nash equilibrium (BNE) of the game is investigated. Since the equilibrium is Pareto inefficient, we propose a pricing policy to the resource control game by adding a penalty price to user's transmission cost. With the adoption of the price, user's aggressive behavior is depressed, and Pareto improvement is achieved. Also the Pareto efficient BNE of the game with pricing is studied. Simulation results show that users can obtain higher throughput and lower average packet transmission delay by proper pricing policy. It is also verified that the scheme of pricing policy is robust when information of channel conditions is inaccurate.

In this paper, we propose optimization approaches for the parameter determination of the PNNI complex node model. Two optimal objectives are discussed: Least Square Approximation and Maximum Deviation Minimization. For each objective, we propose two practical criteria for setting up bypasses: Maximum Difference Removal and Largest Deviation Removal. Generalized inverse of matrix and linear programming techniques are used to find the solutions. The numerical results show that the least square approximation with the largest deviation removal criteria has the best performance as the number of bypasses increases.

As a highly efficient radio link technology, the opportunistic scheduling policy has been widely investigated and implemented. Therefore, new challenges come up in the case of TCP over opportunistic scheduling systems. In this paper we investigate the impact of wireless opportunistic scheduling on TCP throughput. It shows that the optimization of the wireless link mechanisms needs to be maintained at the transport layer by cooperation of the adjacent layers. We propose a new ACK Reservoir Method to smooth the TCP behavior combating against the spurious timeout caused by scheduling. Based on performance analysis and simulation results, the proposed method is shown to enhance the TCP throughput by up to 100% in the presence of opportunistic scheduling. Finally, the proposed method is evaluated in a practical simulation scenario of CDMA/HDR system.