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Increasing demand for high-performance 4G broadband wireless is enabled by the use of multiple antennas at both base station and subscriber ends. Multiple antenna technologies enable high capacities suited for Internet and multimedia services, and also dramatically increase range and reliability. In this article we describe a multipleinput multiple-output OFDM wireless communication system, lab test results, and recent field test results obtained in San Jose, California. These are the first MIMO system field tests to establish the performance of MIMO communication systems. Increased capacity, coverage, and reliability are clearly evident from the test results presented in this article.

We propose a maximum-likelihood approach for separating and estimating multiple synchronous digital signals arriving at an antenna array. The spatial response of the array is assumed to be known imprecisely or unknown. We exploit the nite alphabet (FA) property of digital signals to simultaneously determine the array response and the symbol sequence for each signal. Uniqueness of the estimates is established for signals with linear modulation formats. We introduce a signal detection technique based on the FA property which is di erent from a standard linear combiner. Computationally e cient algorithms for both block and recursive estimation of the signals are presented. This new approach is applicable to an unknown array geometry and propagation environment, which is particularly useful in wireless communication systems. Simulation results demonstrate its promising performance.

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This is an author produced version of a paper published in IEEE Transactions on Communications.This paper has been peer-reviewed but does not include the final publisher proofcorrections or proceedings pagination.© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Citation for the published paper: Abstract-Energy-efficient wireless communication is very important for battery-constrained mobile devices. For mobile devices in a cellular system, uplink power consumption dominates the wireless power budget because of RF power requirements for reliable transmission over long distances. Our previous work in this area focused on optimizing energy efficiency by maximizing the instantaneous bits-per-Joule metric through iterative approaches, which resulted in significant energy savings for uplink cellular OFDMA transmissions. In this paper, we develop energy efficient schemes with significantly lower complexity when compared to iterative approaches, by considering time-averaged bits-per-Joule metrics. We consider an uplink OFDMA system where multiple users communicate to a central scheduler over frequency-selective channels with high energy efficiency. The scheduler allocates the system bandwidth among all users to optimize energy efficiency across the whole network. Using timeaveraged metrics, we derive energy optimal techniques in "closed forms" for per-user link adaptation and resource scheduling across users. Simulation results show that the proposed schemes not only have low complexity but also perform close to the globally optimum solutions obtained through exhaustive search.

The two key limiting factors facing wireless systems today are multipath interference and multiuser interference. In this context, a challenging signal processing problem is the joint space-time equalization of multiple digital signals transmitted over multipath channels. We propose a blind approach that does not use training sets to estimate the transmitted signals and the space-time channel. Instead, this approach takes advantage of spatial and temporal oversampling techniques and the finite alphabet property of digital signals to determine the user symbol sequences. The problem of channels with largely differing and ill-defined delay spreads is discussed. The proposed approach is tested on actual channel data. I. INTRODUCTION A challenging problem in signal processing is the blind joint space-time equalization of multiple digital signals transmitted over multipath channels. An important area where such a problem arises is wireless (mobile) communications. Consider a scenario where several users are trying to talk to a central base station, which has several antennas (viz., Fig. 1). A space-time equalizer at the base station combines two signal processing aspects: equalization (or echo canceling) to combat the intersymbol interference due to large-delay multipath and source separation to combat cochannel interference (CCI). The CCI might be interfering signals at the same frequency from neighboring communication cells, or we might intentionally allow multiple users at the same frequency in order to increase the system capacity. The latter is known as space division multiple access (SDMA) because it essentially separates users based on differences in location. Current communication systems such as IS-54 and GSM require some amount of equalization (up to five symbol periods in GSM and up to one symbol period in IS-54) but are not designed to handle cochannel users. To assist "classical" single-user channel identification algorithms, a fair number of training symbols are incorporated in the data packets.

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