Uncompressed HD (high-definition) video delivery over wireless personal area networks (WPANs) is a challenging problem because of the limited bandwidth and variations in channel. The 60 GHz millimeter-wave (mmWave) band has recently drawn much interest because of the huge bandwidth that it can provide from 57-66 GHz unlicensed spectrum available worldwide. However, to date a system design supporting uncompressed HD video over WPAN is still lacking. In this paper, we develop, simulate, and evaluate an mmWave system for supporting uncompressed video streaming over wireless (UVoW). New features of the UVoW system incorporates: (i) UEP (unequal error protection) where different video bits (MSBs and LSBs) are protected differently, (ii) a multi-CRC to determine whether MSB or/and LSB portions are in error, (iii) UV-ARQ, uncompressed video retransmission protocol which allows the receiver to request only those portions of a video packet which have high importance. Simulations indicate that the UVoW system achieves significantly higher video quality than normal systems under various wireless channel conditions. This shows that UVoW is a promising wireless system supporting uncompressed HD video.

In 60 GHz wireless networks, autonomous coordinator selection is required to find a device to coordinate the transmissions among devices. In order to minimize the power consumption for the coordinator, we utilize the direction information extracted from beamformed transmissions in finding the coordinator automatically. The problem is formulated as a K-center problem, which is a NP-hard problem in general. Analysis is carried out to find optimal solutions in certain tractable topologies. Numerical algorithms and simulation results are further presented for random two dimensional topologies.

Uncompressed HD (high-definition) video delivery over wireless personal area networks (WPANs) is a challenging problem because of the limited bandwidth and variations in channel. The most straight forward technique to recover from channel errors is to retransmit corrupted packets. However, retransmissions introduce significant delay/jitter and require additional bandwidth. Therefore, retransmissions may be unsuitable for uncompressed video streaming. In this paper, we develop, simulate, and evaluate an millimeter- wave (mmWave) system for supporting uncompressed video streams up to 3-Gbps without any retransmissions. New features of the mmWave system incorporates: (i) UEP (unequal error protection) where different video bits (MSBs and LSBs) are protected differently, (ii) a multiple-CRC to determine whether MSB or/and LSB portions are in error, (iii) RS code swapping (RSS), an error concealment scheme which can conceal some errors in video pixels. Simulations using real uncompressed HD images indicate that the proposed mmWave system can maintain good average PSNR (peak-signal-to-noise-ratio) under poor channel conditions, achieving what is generally accepted as a good picture quality with PSNR values greater than 40 dB. Moreover, the proposed system results in less fluctuating PSNR values.

We analyze the performance limits of data dissemination with multi-channel, single radio sensors. We formulate the problem of minimizing the average delay of data dissemination as a stochastic shortest path problem and show that, for an arbitrary topology network, an optimal control policy can be found in a finite number of steps, using value iteration or Dijsktra's algorithm. However, the computational complexity of this solution is generally prohibitive. We thus focus on two special classes of network topologies of practical interest, namely single-hop clusters and multi-hop cluster trees. For these topologies, we derive the structure of policies that achieve an average delay within a factor 1 + e of the optimal average delay, in networks with large number of nodes. Through simulation, we show that these policies perform close to optimal even for networks with small and moderate numbers of nodes. Our analysis and simulations reveal that multichannel data dissemination policies lead to a drastic reduction in the average delay, up to a factor as large as the total number of channels available, even though each node can communicate over only one channel at any point of time. Finally, we present the foundations of a methodology, based on extreme value theory, allowing the implementation of our near-optimal dissemination policies with minimal overhead.

In wireless networks, it is well established that the throughput can be increased by opportunistically scheduling transmissions to users that have good channel conditions. Several “opportunistic” medium access control protocols have been developed, which enable distributed users to opportunistically transmit without requiring a centralized scheduler. In this paper, we consider opportunistic splitting algorithms, where a sequence of mini-slots is used to determine the appropriate user to schedule at each time. In prior work, this type of algorithm has been developed for homogeneous systems in which all users have independent and identically distributed (i.i.d.) channel statistics. Here, we specify new splitting algorithms for a heterogeneous environment that may also include fairness constraints. The performance of the splitting algorithms are characterized via analysis and simulations. In particular, we show that in certain cases, a heterogeneous algorithm will perform at least as well as the homogeneous algorithm in a system with the same total number of users.

In wireless fading channels, multiuser diversity can be exploited by scheduling users to transmit when their channel conditions are favorable. This leads to a sum throughput that increases with the number of users and, in certain cases, achieves capacity. However, such scheduling requires global knowledge of every user's channel gain, which may be difficult to obtain in some situations. This paper addresses contention-based protocols for exploiting multiuser diversity with only local channel knowledge. A variation of the ALOHA protocol is given in which users attempt to exploit multiuser diversity gains, but suffer contention losses due to the distributed channel knowledge. The growth rate of the sum throughput for this protocol is characterized in a backlogged system under both short-term and long-term average power constraints. A simple "fixed-rate" system is shown to be asymptotically optimal and to achieve the same growth rate as in a system with an optimal centralized scheduler. Moreover, asymptotically, the fraction of throughput lost due to contention is shown to be 1/e. Also, in a system with random arrivals and an infinite user population, a variation of this ALOHA protocol is shown to be stable for any total arrival rate, given that users can estimate the backlog.

In this paper, we develop distributed approaches for power allocation and scheduling in wireless access networks. We consider a model where users communicate over a set of parallel multi-access fading channels, as in an OFDM or multi-carrier system. At each time, each user must decide which channels to transmit on and how to allocate its power over these channels. We give distributed power allocation and scheduling policies where each user's actions depend only on knowledge of their own channel gains. We characterize an optimal policy which maximizes the system throughput and also give a simpler sub-optimal policy which is shown to have the optimal scaling behavior in several asymptotic regimes.

We develop medium access control protocols to enable users in a wireless network to opportunistically transmit when they have favorable channel conditions, without requiring a centralized scheduler. We consider approaches that use splitting algorithms to resolve collisions over a sequence of minislots, and determine the user with the best channel. First, we present a basic algorithm for a system with i.i.d. block fading and a fixed number of backlogged users. We give an analysis of the throughput of this system and show that the average number of minislots required to find the user with the best channel is less than 2.5 independent of the number of users or the fading distribution. We then extend this algorithm to a channel with memory and also develop a reservation based scheme that offers improved performance as the channel memory increases. Finally we consider a model with random arrivals and propose a modified algorithm for this case. Simulation results are given to illustrate the performance in each of these settings.

Multiuser diversity refers to a type of diversity present across different users in a fading environment. This diversity can be exploited by scheduling transmissions so that users transmit when their channel conditions are favorable. Using such an approach leads to a system capacity that increases with the number of users. However, such scheduling requires centralized control. In this paper, we consider a decentralized medium access control (MAC) protocol, where each user only has knowledge of its own channel gain. We consider a variation of the ALOHA protocol, channel-aware ALOHA; using this protocol we show that users can still exploit multiuser diversity gains. First we consider a backlogged model, where each user always has packets to send. In this case we show that the total system throughput increases at the same rate as in a system with a centralized scheduler. Asymptotically, the fraction of throughput lost due to the random access protocol is shown to be 1/e. We also consider a splitting algorithm, where the splitting sequence depends on the users' channel gains; this algorithm is shown to approach the throughput of an optimal centralized scheme. Next we consider a system with an infinite user population and random arrivals. In this case, it is proved that a variation of channel-aware ALOHA is stable for any total arrival rate in a memoryless channel, given that users can estimate the backlog. Extensions for channels with memory are also discussed.