This article consists of a collection of slides from the author's conference presentation.

In this paper, we present a methodology to analytically compute the end-to-end throughput that can be achieved on a path between two nodes in an IEEE 802.11 multihop wireless network with homogenous data transmission rates. Knowledge of achievable end-to-end throughput is important for making routing decisions and performing admission control. Unlike a wired network where the throughput of a path after accounting for overheads is roughly equal to the lowest bandwidth along the path, the throughput of a wireless multihop path is much lower than the minimum data rate along the path because of sharing of the medium by nodes within carrier sensing range of each other. Our analysis of the achievable throughput takes into account this effect of sharing of the medium in the form of blocking and interference. We apply our analysis to several randomly generated paths, and compare the analytical results with those from simulations to validate the analysis.

In this paper, we consider optimization of CSMA/CA based wireless networks such as IEEE 802.11 Wireless LANs. A fundamental component of the MAC layer functionality in such networks is the binary exponential backoff (BEB) of contending nodes which serves as a means of arbitrating distributed channel access. In this paper, we show that the joint optimization of initial contention window (CWmin) and the number of backoff stages in BEB yields, interestingly, no additional gains over a simple CWmin optimization that is performed by considering that BEB is absent. Thus, BEB has negligible impact once CWmin is optimized. While this result holds only for an ideal WLAN, in the presence of channel errors, BEB penalizes performance even when CWmin is optimized. Finally, disabling BEB and optimizing CWmin not only improves short-term fairness significantly but it also stabilizes the system even when there are asymptotically large number of saturated users contending.

Most current deployments of IEEE 802.11 based wireless LANs suffer from various inefficiencies arising from the interactions of MAC and Physical layers. These inefficiencies often limit network users from reaping the full potential of the high physical data rates in these systems. We consider optimizing these systems to mitigate, the following forms of inefficiencies: (i) selfish users exploiting the dependency of DCF channel share achieved on the transmission strategies used, leading to inefficient operating points (Nash Equilibria) (ii) Automatic rate adaptation enabled devices reducing the system throughput even for moderate loads, and, (iii) low data rate users limiting the throughput of high data rate users. In the companion paper, we have proposed adapting CWmin and disabling Exponential Backoff as a simple paradigm of operating CSMA/CA. We show that such a technique is effective in reducing the penalty due to selfish link adaptation and auto rate adaptation. Finally, we propose using multiple channels to improve the throughput of high data rate users. We show that the system throughput can increase super-linearly with the number of channels, with increased benefit when OFDM based IEEE 802.11g high rate users co-exist with low rate IEEE 802.11b users.

A critical factor in the deployment of multiple-input multiple-output (MIMO) systems is the cost of multiple analog transmit/receive chains. This problem can be mitigated by antenna subset selection at the transmitter/receiver. With antenna selection, a small number of analog chains are multiplexed between a much larger number of transmit/receive antenna elements. In this paper, we present a low complexity approach to receive antenna selection for capacity maximization, based on the theory of convex optimization. We show via extensive Monte-Carlo simulations that the proposed algorithm provides performance very close to that of optimal selection based on exhaustive search. We also, extend this approach to receive antenna selection for the JMMSE and OSIC V-BLAST architectures

We consider the following two views of an IEEE 802.11 based Wireless LAN: (i) as seen by the WLAN medium and (ii) as seen by a user. In the system centric view, we model the WLAN medium as a server that allocates its resources to users in a round Robin manner. This resource sharing model not only provides a simple model for the system, it also enables us to derive the channel service rate and the total delay incurred in transmitting a packet. For Poisson arrivals, the resource sharing model takes the form of an M/G/1/PS system with the mean delay being the same as that in an equivalent M/M/1 system. We then take a user centric view and model each user's queue as a separate G/G/1 queue. We derive the probability distributions for the different delay sources, i.e., random back-off time, random number of collisions and random number of successful transmissions from other users. This user centric model can provide insights into understanding access and queuing delays in 802.11 DCF. Finally, we discuss the utility of these models for functions such as capacity analysis, admission control and QoS enforcement.

In this paper, we present a simple analytical framework for computing the throughput of IEEE 802.11 based wireless LANs. We show that a notion of average cycle time exists in DCF access where by all stations, on average, successfully transmit one packet in a cycle. We provide explicit expressions for the average cycle time and the system throughput. Our approach readily depicts that the average cycle time, and hence the throughput, is the same for different users regardless of the differences in their physical data rates. It thus serves as a simple and accurate re-derivation of the well known equal throughput property of DCF seen in multi-rate WLANs. Our analytical results are compared against extensive simulations and are shown to be in very good agreement

IEEE 802.11 based wireless local area networks (WLANs) are becoming popular in home, enterprise and public access areas primarily due to their low cost, simplicity of installation and high data rates. While WLANs continue to be predominantly data centric, there is growing interest in using WLANs for voice, especially in enterprise markets. This paper presents new analytical and simulation results for the conversational speech capacity of WLANs and compares the different WLAN technologies in that regard. Specifically, we consider IEEE 802.11b, 802.11a and 802.11g systems in the infrastructure mode and find that voice capacity is a strong function of the channel bandwidth, codec packetization interval, data traffic and the packet size used by data. For the IEEE 802.11g system, we find that capacity depends on the CTS-to-self and RTS-CTS legacy protection mechanisms, with the RTS-CTS mechanism achieving lower capacity. We show that the analytical results are in close agreement with those from simulations and conclude the paper by highlighting some key factors that dictate the capacity of WLANs.