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This paper introduces a novel analytical model for analyzing the performance of handoff algorithms based on absolute and relative signal strength measurements. The performance is analyzed in multicell and multisector environments where cochannel interference (CCI) is present. The model presented in this paper accounts for the distinct features of intersector handoff compared with intercell handoff. Numerical results show that the performance metrics are affected by the CCI level. The occurrence condition of unnecessary handoffs in multisector systems is also presented. [ABSTRACT FROM AUTHOR]

This paper considers a scheduling problem for multi-user transmissions over the downlink of a time-slotted cellular data network. For such a network, opportunistic scheduling exploits the time-varying radio channel and improves network performance. This paper presents a new scheduling solution that maximizes the aggregate user performance subject to certain minimum and maximum performance constraints. By constraining the performance experienced by individual users, who share a common radio downlink, to some upper bounds, it is possible to provide the system operator with a better control of radio resource allocations and service differentiation among different classes of users. The proposed solution, which is referred to as Throughput Constrained Opportunistic Scheduling (TCOS), offers better service differentiation among different classes of users than the existing opportunistic scheduling algorithms with only minimum performance constraints. For ideal memoryless fading channels, TCOS provides performance comparable with an existing scheme with minimum and maximum performance constraints. For realistic fading channels with memory, TCOS significantly improves system performance due to its ability to trade off feasibility with throughput. Extensive simulation results demonstrate the improved system performance and effective service differentiation of the proposed solution under realistic channel conditions. [ABSTRACT FROM AUTHOR]

In this paper, we develop optimization techniques for linear zero-forcing (ZF) multiple-input, multiple-output (MIMO) broadcast (BC) precoders. A computationally efficient technique based on QR-update algorithms for implementing this optimization is then proposed. The application of the proposed ZF precoders and decoders to systems with both large and small numbers of users is considered. The proposed optimization technique is also shown to perform very well in conjunction with nonlinear Tomlinson- Harashima precoding. Both coded and uncoded performances are considered. [ABSTRACT FROM AUTHOR]

Several channel-allocation algorithms have been pro- posed in the literature for traditional cellular networks with static base stations (BS5), while not much attention has been given to channel-allocation problems for cellular networks where BSs are mobile. In cellular networks with mobile BSs (MBSs), the network topology is dynamic due to the mobility of the BSs. This makes the channel-allocation problem in such networks more challenging. Moreover, the MBSs may fail and degrade the performance of the cellular network. Therefore, it is desirable that the channel- allocation algorithm be fault tolerant. Thus, even in the presence of failure of the MBSs, the channel-allocation algorithm should work reasonably well. It is also desirable to design a channel-allocation approach that guarantees that the request from a mobile host (MH) is responded to in a timely manner. In this paper, a distributed dynamic channel-allocation algorithm that addresses these problems in cellular networks with MBSs is proposed. The proposed algorithm is fault tolerant and guarantees that the time to respond to an MH's request for supporting a call is upperbounded. The performance evaluation of the proposed algorithm shows that the proposed algorithm performs well, even in the presence of failure of the MBSs. [ABSTRACT FROM AUTHOR]

Video transmission over unreliable channels may suffer from the data loss or corruption. To facilitate the transmission, video content is compressed to save the bandwidth. The compression algorithms remove the redundancies in the video signal, meanwhile increasing the dependencies among symbols in the compressed bit-stream. Thus, when errors occur, they may propagate in both space and time. Among various error control techniques, error concealment (EC) is an effective method that is performed at the decoder to mitigate the influence of errors on the quality of reconstructed images. In this paper, a joint spatial and temporal EC algorithm (JSTEC) is presented. First, several existing temporal EC algorithms are combined in an appropriate order. Then, the spatial correlation in the video is exploited in an iterative form to improve the performance of the temporal EC. Experimental results show that JSTEC performs better both in peak signal-to-noise ratio and subjective quality of images than the existing algorithms. [ABSTRACT FROM AUTHOR]

Fast adaptive transmission has been recently identified as a key technology for exploiting potential system diversity and improving power-spectral efficiency in wireless communication systems. In this paper, an adaptive resource-allocation approach, which jointly adapts subcarrier allocation, power distribution, and bit distribution according to instantaneous channel conditions, is proposed for multiuser multiple-input multiple-output (MIMO)/orthogonal frequency-division multiplexing systems. The resultant scheme is able to: 1) optimize the power efficiency; 2) guarantee each user's quality of service requirements, including bit-error rate and data rate; 3) ensure fairness to all the active users; and 4) be applied to systems with various types of multiuser-detection schemes at the receiver. For practical implementation, a reduced-complexity allocation algorithm is developed. This algorithm decouples the complex multiuser joint resource-allocation problem into simple single-user optimization problems by controlling the subcarrier sharing according to the users' spatial separability. Numerical results show that significant power and diversity gains are achievable, compared with non-adaptive systems. It is also demonstrated that the MIMO system is able to multiplex several users without sacrificing antenna diversity by using the proposed algorithm. [ABSTRACT FROM AUTHOR]