Sum power iterative water-filling (SPIWF) algorithm provides sum-rate-optimal transmission scheme for wireless multiple-input multiple-output (MIMO) broadcast channels (BC), whereas it suffers from its high complexity. In this paper, we propose a new transmission scheme based on a novel block zero-forcing dirty paper coding (Block ZF-DPC) strategy and multiuser-diversity-achieving user selection procedure. The Block ZF-DPC can be considered as an extension of existing ZF-DPC into MIMO BCs. Two user selection algorithms having linear increasing complexity with the number of users have been proposed. One aims at maximizing the achievable sum rate directly and the other is based on Gram-Schmidt Orthogonalization (GSO) and Frobenius norm. The proposed scheme is shown to achieve a sum rate close to the sum capacity of MIMO BC and obtain optimal multiplexing and multiuser diversity gain. In addition, we also show that both selection algorithms achieve a significant part of the sum rate of the optimal greedy selection algorithm at low computation expenditure.

This paper proposes a MAC protocol for efficient broadcasting in wireless ad hoc networks. Pure flooding leads to serious redundant broadcasts, packet contention and packet collisions, known as the broadcast storm problem. This paper focuses on how to reduce the redundant broadcasts. Several protocols to achieve efficient broadcasting have been proposed. However a trade-off exists between the reachability and the broadcasting ratio, which is the ratio of the number of the broadcasting nodes to the number of received nodes. This paper proposes a new MAC protocol for on-demand broadcasting, which is referred to as dialogue-based protocol in order to resolve the trade-off. The dialogue-based protocol employs additional massages which are called as request packets and reply signals. They are exchanged in an on-demand manner, in order that relay candidate nodes recognize its neighbor nodes status whether they have already received the broadcast packets. Finally, by computer simulations, this paper presents that the dialogue-based scheme combines high reachability with low broadcasting ratio by using the low additional massages.

In this letter, we propose two computationally efficient precoding algorithms that achieve near-ML performance for multiuser MIMO downlink. The proposed algorithms perform tree expansion after lattice reduction. The first full expansion is tried by selecting the first level node with a minimum metric, constituting a reference metric. To find an optimal sequence, they iteratively visit each node and terminate the expansion by comparing node metrics with the calculated reference metric. By doing this, they significantly reduce the number of undesirable node visit. Monte-Carlo simulations show that both proposed algorithms yield near-ML performance with considerable reduction in complexity compared with that of the conventional schemes such as sphere encoding.

Satellite broadcasting in the 21-GHz band is expected to transmit large-capacity signals such as ultrahigh-definition TV. However, this band suffers from large amounts of rain attenuation. In this regard, we have been studying rain fading mitigation techniques, in which the radiation power is increased locally in the area of heavy rainfall. To design such a satellite broadcasting system, it is necessary to evaluate service availability when using the locally increased beam technique. The rain attenuation data should be derived from the rainfall rate data. We developed a method to transform rainfall rate into rain attenuation in the 21 GHz band. Then, we performed a simulation that applied the method to the analysis of the service availability for an example phased array antenna configuration. The results confirmed the service availability increased with the locally increased beam technique.

This letter presents a simple joint estimation method for residual frequency offset (RFO) and sampling frequency offset (STO) in OFDM-based digital video broadcasting (DVB) systems. The proposed method selects a continual pilot (CP) subset from an unsymmetrically and non-uniformly distributed CP set to obtain an unbiased estimator. Simulation results show that the proposed method using a properly selected CP subset is unbiased and performs robustly.

This paper presents a new QoS model for end-to-end service provisioning in multi-hop wireless networks. In legacy IEEE 802.11e based multi-hop wireless networks, the fixed assignment of service classes according to flow's priority at every node causes priority inversion problem when performing end-to-end service differentiation. Thus, this paper proposes a new QoS provisioning model called Dynamic Hop Service Differentiation (DHSD) to alleviate the problem and support effective service differentiation between end-to-end nodes. Many previous works for QoS model through the 802.11e based service differentiation focus on packet scheduling on several service queues with different service rate and service priority. Our model, however, concentrates on a dynamic class selection scheme, called Per Hop Class Assignment (PHCA), in the node's MAC layer, which selects a proper service class for each packet, in accordance with queue states and service requirement, in every node along the end-to-end route of the packet. The proposed QoS solution is evaluated using the OPNET simulator. The simulation results show that the proposed model outperforms both best-effort and 802.11e based strict priority service models in mobile ad hoc environments.

This paper presents discussion about channel fluctuation on channel estimation in digital terrestrial television broadcasting. This channel estimation uses a two-dimensional (2D) filter. In our previous work, only a structure of a lattice is considered for generation of nonrectangular 2D filter. We investigate generation of nonrectangular 2D filter with adaptive method, because we should refer to not only a lattice but also channel conditions. From the computer simulations, we show that bit error rate of the proposed filter is improved compared to that of the filter depending on only lattices.

Vector precoding is a nonlinear broadcast precoding scheme in the downlink of multi-user MIMO systems which outperforms linear precoding and THP (Tomlinson-Harashima Precoding). This letter discusses the problem of joint receive antenna selection in the multi-user MIMO downlink with vector precoding. Based on random matrix analysis, we derive a simple heuristic selection criterion using singular value decomposition (SVD) and carry out an exhaustive search to determine for each user which receive antenna should be used. Simulation results reveal that receive antenna selection using our proposed criterion obtains the same diversity order as the optimal selection criterion.

In order to achieve the prioritized quality of service (QoS) guarantee, the IEEE 802.11e EDCAF (the enhanced distributed channel access function) provides the distinguished services by configuring the different QoS parameters to different access categories (ACs). An admission control scheme is needed to maximize the utilization of wireless channel. Most of papers study throughput improvement by solving the complicated multidimensional Markov-chain model. In this paper, we introduce a backoff model to study the transmission probability of the different arbitration interframe space number (AIFSN) and the minimum contention window size (CWmin). We propose an adaptive control scheme (ACS) to dynamically update AIFSN and CWmin based on the periodical monitoring of current channel status and QoS requirements to achieve the specific service differentiation at access points (AP). This paper provides an effective tuning mechanism for improving QoS in WLAN. Analytical and simulation results show that the proposed scheme outperforms the basic EDCAF in terms of throughput and service differentiation especially at high collision rate.

We investigate the MIMO broadcast channels with imperfect channel knowledge due to estimation error and much more users than transmit antennas to exploit multiuser diversity. The channel estimation error causes the interference among users, resulting in the sum-rate loss. A tight upper bound of this sum-rate loss based on zeroforcing beamforming is derived theoretically. This bound only depends on the channel estimation quality and transmit antenna number, but not on the user number. Based on this upper bound, we show this system maintains full multiuser diversity, and always benefits from the increasing transmit power.

We propose a new broadcast strategy for a multiple-input multiple-output (MIMO) system with N transmit antennas at the transmitter and M≤N single antenna receivers. The proposed method, based on dirty-paper coding (DPC), spatially separates the M users but does not suffer from the power loss of classical spatial division multiple access (SDMA). For the special case of M=N=2 and when the two single antenna receivers are assumed to be co-located, the proposed scheme produces a 2 transmit, 2 receiver antenna MIMO transmission system that doubles the symbol rate of MIMO space-time block code (STBC) systems from one to two symbol per transmission time. It is proved theoretically and experimentally that the proposed scheme provides the same performance level as that of MIMO STBC systems (i.e., the Alamouti scheme) for the first symbol, and the same performance as the Bell labs layered space-time (BLAST) system for the second symbol. When compared to the BLAST system, the proposed scheme has the same symbol rate, but achieves significantly better performance, since it provides 2 level diversity per symbol on the first symbol while the BLAST system does not provide any diversity.

Energy-efficiency is one of the main concerns in the wireless information dissemination system. This paper presents a wireless broadcast stream organization scheme which enables complex queries (e.g., aggregation queries) to be processed in an energy-efficient way. For efficient processing of complex queries, we propose an approach of broadcasting their pre-computed results with the data stream, wherein the way of replication of index and pre-computation results are investigated. Through analysis and experiments, we show that the new approach can achieve significant performance enhancement for complex queries with respect to the access time and tuning time.

Based on an analysis of the error patterns in lattice-reduction (LR) precoding in a multiple-antenna broadcast channel, this paper proposes a simple precoding technique that can reduce the quantization error. The proposed scheme establishes a lattice list to provide more candidates for transmission power reduction based on the analysis of the patterns of the error in the LR precoding method [9]. Simulation results show that the proposed scheme matches the BER performance of more complex precedents (such as the vector perturbation using sphere encoding) with significant saving in complexity.

In this paper, we investigate the critical low coverage problem of position aware localized efficient broadcast in mobile ad hoc ubiquitous sensor networks and propose a generic framework for it. The framework is to determine a small subset of nodes and minimum transmission radiuses based on snapshots of network state (local views) along the broadcast process. To guarantee the accuracy of forward decisions, based on historical location information nodes will predict neighbors' positions at future actual transmission time and then construct predicted and synchronized local views rather than simply collect received "Hello" messages. Several enhancement technologies are also proposed to compensate the inaccuracy of prediction and forward decisions. To verify the effectiveness of our framework we apply existing efficient broadcast algorithms to it. Simulation results show that new algorithms, which are derived from the generic framework, can greatly increase the broadcast coverage ratio.

We propose a new Multimedia-on-Demand (MoD) system which provides broadcast, batch and interactive services concurrently. An analytical model is derived for the performance evaluation of this MoD system. Numerical results show that with proper design the system can provide better system performance than some previously proposed MoD systems.

This letter introduces a simple way of estimating the integer frequency offset (IFO) of OFDM-based digital video broadcasting (DVB) systems. By modifying the conventional maximum likelihood (ML) estimator to include the multi-stage estimation strategy, the IFO estimator is derived. Simulations indicate that the proposed IFO estimator works robustly when compared to ML estimator.

The power reduction of display devices has become an important issue for extending battery life and running time when they are used in digital multimedia broadcasting (DMB) mobile phones. DMB mobile phones generally use 16-bit data per pixel to reduce power consumption even though a liquid crystal display (LCD) graphic controller can support 16-, 18-, and 24-bit data per pixel. Also, the total transmission time of 16-bit data per pixel is only half that for 18- and 24-bit data per pixel. Decoded 24-bit image data in the frame memory of a DMB decoder are asymmetrically truncated to 16-bit image data. This results in a lack of smoothness such as blocking effects and/or pseudo edge artifacts. To solve these problems, the author proposes and implements a new asymmetric pixel data truncation error compensation algorithm using 1-bit least significant bit (LSB) data expansion with correlated color information for the purpose of ensuring smoothness. In the experimental results, the proposed algorithm is able to correct various artifacts.

In mobile computing environments, cache invalidation techiniques are widely used. However, theses techniques require a large-sized invalidation report and show low cache utilization under high server update rate. In this paper, we propose a new cache-level cache invalidation technique called TTCI (Timestamp Tree-based Cache Invalidation technique) to overcome the above two problems. TTCI also supports selective tuning for a cache-level cache invalidation. We show in our experiment that our technique requires much smaller size of cache invalidation report and improves cache utilization.

This letter proposes a group-based distributed air index (called GDI) using two-leveled groups by partitioning the identifiers of data items to reduce the size of the index. GDI provides both global and local views of data items and multiple pointers to data items in a single access to an index. Simulation results show that GDI outperforms the existing index in terms of multiple data access, energy conservation and data waiting time.

Channel state information (CSI) at transmitter plays an important role for multiuser MIMO broadcast channels, but full CSI at transmitter is not available for many practical systems. Previous work has proposed orthonormal random beamforming (ORBF) [16] for MIMO broadcast channels with partial channel state information (CSI) feedback, and shown that ORBF achieves the optimal sum-rate capacity for a large number of users. However, for cellular systems with moderate number of users, i.e., no more than 64, ORBF only achieves slight performance gain. Therefore, we analyze the performance of ORBF with moderate number of users and total transmit power constraint and show that ORBF scheme is more efficient under low SNR. Then we propose an adaptive ORBF scheme that selects the number of random beams for simultaneous transmission according to the average signal-to-noise ratio (SNR). Moreover, a multi-beam selection (MBS) scheme that jointly selects the number and the subset of the multiple beams is proposed to further improve the system performance for low SNR cases. The simulation results show that the proposed schemes achieve significant performance improvement when the number of users is moderate.