Adaptive modulation and MIMO coding for broadband wireless datanetworks

Link adaptation techniques, where the modulation, coding rate, and/or other signal transmission parameters are dynamically adapted to the changing channel conditions, have emerged as powerful tools for increasing the data rate and spectral efficiency of wireless data-centric networks. While there has been significant progress on understanding the theoretical aspects of time adaptation in LA protocols, new challenges surface when dynamic transmission techniques are employed in broadband wireless networks with multiple signaling dimensions. Those additional dimensions are mainly frequency, especially in multicarrier systems, and space in multiple-antenna systems, particularly multiarray multiple-input multiple-output communication systems. We give an overview of the challenges and promises of link adaptation in future broadband wireless networks. We suggest guidelines to help in the design of robust, complexity/cost-effective algorithms for these future wireless networks     

Attainable throughput of an interference-limited multiple-inputmultiple-output (MIMO) cellular system

We investigate the high spectral efficiency capabilities of a cellular data system that combines the following: 1) multiple transmit signals, each using a separately adaptive modulation; 2) adaptive array processing at the receiver; and 3) aggressive frequency reuse (reuse in every cell). We focus on the link capacity between one user and its serving base station, for both uncoded and ideally coded transmissions. System performance is measured in terms of average data throughput, where the average is over user location, shadow fading, and fast fading. We normalize this average by the total bandwidth, call it the mean spectral efficiency, and show why this metric is a useful representation of system capability. We then quantify it, using simulations, to characterize multiple-input multiple-output systems performance for a wide variety of channel conditions and system design options     

Some results and insights on the performance gains of MIMO systems

Multiple-input-multiple-output (MIMO) systems generally fall into two categories, depending on the kind of gain they provide: spatial multiplexing (SM) methods yield capacity gain and diversity methods yield link quality gain [measured here by the post-processing signal-to-noise ratio (SNR)]. We consider a set of systems from each category, quantify their gains analytically or via simulations, and show how these gains vary with the receiver input SNR and the numbers of antennas. The contribution of this work resides in both the closed-form analytical results and the numerical comparisons. We both highlight the benefits of using additional transmit antennas and provide comparisons among diversity-based and SM-based MIMO schemes. The analytical results are for a diversity-based scheme that combines selection diversity at the transmit side with maximum ratio combining (MRC) at the receive side, which we show to upper bound the SNR performance of other diversity-based schemes. We find that, for practical system parameters, the relevant SNR metric is 6-12 dB higher for the diversity-based schemes than for SM-based schemes. At the same time, SM-based schemes yield capacity metrics which range from 30% higher to double that of diversity-based schemes.     

Simulation results for an interference-limited multiple-inputmultiple-output cellular system

We describe a simulation study of a cellular system using multiple-input multiple-output (MIMO) antenna techniques along with adaptive modulation and aggressive frequency reuse. We show for the case of 3 transmit and 3 receive antennas, how much MIMO systems outperform systems with receive-diversity-only when noise dominates. When co-channel interference from surrounding cells dominates, the differences shrink, as do the absolute numbers. We quantify these reductions for the specific cases studied, and discuss further areas of research