Wireless systems - Part I

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Introduction

The principle of wireless system design is to transfer information from source to destination without a physical (wired) medium. This is the primary goal. How efficiently can one do this is the design challenge, therein brings in different technology to approach. So how do we define the efficiency metrics ? The resource or the medium to transfer the data or information is the limited spectrum for a limited time. Given a limited Spectrum-time plane, are we allowed to transmit or use this resource at any spatial location? This factor governs the amount of power you are allowed to transmit with. This leads to define a metric in terms of information/Hz/s/watt.

A little bit more on Metric

Design of a “scheme” – A chain of post-processing stages applied on the information before transmitting as electrical waveforms and later into electro-magnetic waveform, has been a historical area of research for all wireless communication experts. Many classical work has been published to maximize efficience of a particular stage. For e.g, optimal M-ary QAM mapping of constellation, capacity bounds on performance on error-control-codes, optimal design of RF filters to reduce emission of energy out of the alloted band, design of antennas such that maximal energy transfer between electrical signal and EM waves is accomplished. Not all the stages are independent of the preceding and following stages. For e.g, packing more information bits into a complex constellation might not have constant envelop which might be stringent requirement on the linearity of the power-amplifier.

The optimal scheme is also a function of the operating point of the spectrum for e.g., one might achieve a “x”/Hz/s/Watt for a spectrum centered at 800MHz, while the same metric is different for spectrum centered at 2GHz. Second, the acheivable metric is also a function of the spatial distribution of stationary and non-stationary elements (like building, moving vehicles, rain, greenary) in the wireless medium. For e.g. in a urban city one might achieve a better “information transfer metric” compared to an open-air/land rural area. Hence, the optimal design is actually not optimal for all time, place and spectrum. This leads to any adaptive optimal designs which can tune the different “stages” for optimization. Ofcourse this needs a “feedback” mechanism to tune them. For example, when the received signal energy decreases due to a path-loss or shadowing loss – the receiver can request to increase the transmit power, reduce the constellation size, increase more error-correcting bits to decode the information, wait for conditions to improve and transmit a burst of information, retransmit information through alternate “path” to increase the detection probability. So one has many approaches to address or acheive a target “metric”. Sometimes (many times) some solutions have practical limitations due to the tx/rx implementation or the technique itself. For e.g, the steps at which power control is applied, fractional modulation size (e.g 3-PSK, 10-qam) are not conventional bit packing schemes. 

To be continued..