Abstract:
This invention presents a MIMO wireless sensor networks communication, which is expected to utilize a larger of size sensor nodes in commercial environments, potentially hostile and militarily sensitive environments. Every sensor node of the MIMO sensor networks communication is to support data collection, signal processing and analysis, and transmission fashion. The present invention also develops novel approaches of advanced space-time processing with the MIMO sensor-antenna architecture, spread spectrum, and adaptive communication signal processing that simultaneously exploit temporal and spatial diversity for seamless sensor networks communications, thereby converting spatially distributed sensor nodes into efficient, robust, reliable, and secure wireless sensor networks communications.

Description:
BACKGROUND 
   This invention is generally relative to a Multiple Input Multiple Output Multiple-Input Multiple-Output wireless sensor networks communication. 
   Conventional deployments of sensor networks communication often scatter multiple sensors over a limited geographic region in order to collect data of interest. The collected data is then analyzed to expeditiously achieve or facilitate a given mission objective. It does not matter whether the collected data is continued surveillance, reconnaissance, target identification, registration and disposition, or anything else along those lines. In the sensor networks communication, each sensor device is expected to reliably and securely transmit its data to a communication receiver for further analysis, pattern recognition, coordination, and processing during various time intervals. Usually, each sensor has a single antenna while the communication receiver is equipped with an antenna array, which has many elements. Different sensors in the sensor networks communication may be responsible for different levels of throughput and fidelity depending on a particular task. In addition, some sensors in the sensor networks communication may have to provide several transmissions within a short-time interval while as other sensors may only transmit at irregular intervals or even not at all. Thus, resource allocations of the sensor networks communication need be determined and continually reassessed so that accommodations of such versatility can be achieved in performance. 
   The further sensor networks communications are envisioned to contain a large number of sensor nodes, each capable of some limited computation, communication and sensing capabilities, operating in an unattended mode with limited energy. They are also characterized by severe energy constraints because the sensor nodes will often operate with finite battery resources and limited recharging. Generally speaking, they have the following properties: (1) A sensor network communication is composed of a large number of sensor nodes that are densely deployed either inside the phenomenon or very close to it; (2) Sensor nodes in the sensor networks communications are prone to failures; (3) A topology of the sensor networks communications changes very frequently; (4) Sensor nodes in the sensor networks communications mainly use a broadcast communication paradigm; (5) Sensor nodes in the sensor networks communications are limited in power, computational capacities, adaptive communication signal processing, transmission, and memory; and (6) in addition, in some cases, sensor nodes of the sensor networks communications may not have global identification because the sensor networks communications use a larger amount of overhead and large number of sensors. 
   A sensor networks communication has numerous applications. One of the applications is used to monitor and control safely critical military and governmental environments such as domestic infrastructure systems. In this case, the application may include battlefield detection and protection systems for biological, chemical and/or radiological weapons, aiding areas hit by disasters. Another of the applications is used for homeland security at airports, bridges, public building, and major subway train systems. A third-one of the applications is used for tracking. For example, a ship in the ocean emits sounds that may be detected and characterized by several underwater senor networks. As the ship moves, the bearing measurements slowly change. A fourth-one of the applications is in smart spaces that may include semiconductor and/or manufactory facilities, smart building, cities, and even sensitive laboratories. A fifth-one of the applications is used to monitor ground temperature such as a forest to detect fast moving forest fires. A sixth-one of the applications is in entertainment environments including amusement parks and/or museums. In addition, other applications are in health case systems such as higher-age health monitor and/or patient health and movement status at home environment. As can be seen, the sensor networks communication has tremendous application value not only in military battlefield but also in commercialization. 
   Recent advances in integrated circuits technology have enabled mass production of tiny, cost-effective, and energy-efficient seamless sensor devices with processing capabilities. The seamless sensor devices are usually equipped with a sensor module in which detects via electrical/electromagnetic fields, acoustics, optical, movement, chemicals, biological agents, radiation, environmental factors such as humidity, temperature, and so on. Characteristics of the seamless sensor devices to be considered are size, battery consumption, energy level, lifetime, movement whether a sensor is mobile or must remain stationary, position that the sensor may be embedded or may be independent of its surroundings, redundancy for checking integrity, and failure modes. The malfunctions may indicate that the sensor has failed, is degrading slowly, or possesses a bad behavior such as going up and down randomly. 
   Advanced sensor networks communication is expected to utilize a larger of size sensor nodes, such as 1000, or even more individual sensor nodes in potentially hostile and militarily sensitive environments. Every sensor node of the sensor networks communication is likely to support data collection and transmission in an efficient, robust, reliable and secure communication fashion. The sensor network communication will encounter to have multipath propagation because sensor network elements are not likely to be guaranteed a line-of-sight transmission path to a communication receiver, which is not promised to remain at a fixed position for any period of time. The multipath propagation arises from scattering, reflection, refraction or diffraction of the radiated energy off objects in the environment. Thus, received signals from sensor nodes are much weaker than transmitted signals due to mean propagation loss. In addition to a mean path loss, the received signals exhibit fluctuations in a signal level that is referred to fading. Moreover, the sensor networks communication may also have interference, such as co-channel interference (CCI), adjacent-channel interference (ACI), and intersymbol interference (ISI). On the other hand, the sensor networks communication may likely have jam resistant in a hostile and militarily sensitive or a battlefield. Therefore, to effectively operate under the abovementioned constraints, we invent using adaptive novel communication signal processing approaches of space-time processing along with MIMO-based multi-sensor code division multiple access (CDMA) architecture for the sensor networks communication. 
   The present invention of the MIMO-based wireless sensor networks communication is not only responsible for frequency selection, carrier frequency generation, interleaver, error coding, channel estimate, signal detection, modulation, and source data encryption as well as strategies that overcome signal multipath propagation effects, but also responsible for architecture schemes including tiny, low-power, low-cost communication transceiver, sensing, analog-to-digital (A/D) and digital-to-analog (D/A) converters, and computing processing units and low power-efficient methods. Thus, there is a continuing need of the MIMO-based wireless sensor networks communication. 
   SUMMARY 
   In accordance with one aspect, a multiple-input multiple-output wireless sensor networks communication system comprises N wireless sensor node and transceiver systems, where N is an integer; each of the wireless sensor node and transceiver systems coupled to M antennas, where M is an integer; a wireless multiple-input multiple-output space-time sensor basestation system coupled to a sensor network interface that is connected to a sensor network; and wireless multiple-input multiple-output space-time sensor basestation system coupled to P antennas, where P is an integer. 
   Other aspects are set forth in the accompanying detailed description and claims. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a block diagram of showing a MIMO wireless sensor networks communication according to some embodiments. 
       FIG. 2  is a block diagram of showing MIMO wireless sensor node structure and transceiver architecture according to some embodiments. 
       FIG. 3  is a detailed block diagram of showing a MIMO transceiver according to some embodiments. 
       FIG. 4  is a detailed block of showing a FEC, interleaver, and spreading of the MIMO transceiver according to some embodiments. 
       FIG. 5  is a detailed block diagram of showing a space-time encoding of the MIMO transceiver according to some embodiments. 
       FIG. 6  is a block diagram of showing a MIMO sensor basestation according to some embodiments. 
       FIG. 7  is a detailed block diagram of showing a space-time processor and decoding of the MIMO sensor basestation according to some embodiments. 
   

   DETAILED DESCRIPTION 
   Some embodiments described herein are directed to the MIMO wireless sensor networks communication transceiver system. It may be implemented in hardware, such as in an Application Specific Integrated Circuits (ASIC), digital signal processor, field programmable gate array (FPGA), software, or a combination of hardware and software. 
   MIMO Wireless Sensor Networks Communication System 
   A MIMO sensor networks communication transceiver system  100  for wireless communications is shown in  FIG. 1  in accordance with one embodiment of the present invention. A number of K wireless sensor nodes and transceiver systems from  110   a  to  110   k  can simultaneously communicate with a MIMO sensor basestation  140 . The wireless sensor node and transceiver  110   a  transmits and receives signals through its multiple antennas from  110   aa  to  110   ak . The MIMO sensor basestation  140  communicates with the wireless sensor node and transceiver  110   a  through its multiple antennas of  130   a  to  130   m . In a similar way, other wireless sensor nodes and transceivers of  110   b  to  110   k  also transmit and receive the information data through their multiple antennas, respectively, and communicate with the MIMO sensor basestation  140  through the multiple antennas of  130   a  to  130   m . The MIMO sensor basestation  140  is coupled to a sensing network interface  150 , which is also connected with a sensor network  160  for processing data information. 
   The MIMO sensor basestation  140 , with knowing all of pseudorandom sequences of the wireless sensor nodes and transceivers of  110   a  to  110   k , can transmit and receive all of information data from all of the wireless sensor nodes and transceivers of  110   a  to  110   k  by spreading and despreading of the wireless sensor&#39;s pseudorandom sequences. The MIMO sensor basestation  140  can use a BPSK or a QPSK or other modulations to transmit and to receive the information data rate on one frequency band. In the present invention, because of using of the multiple antennas in the wireless sensor nodes and transceivers from  110   a  to  110   k  and the MIMO sensor basestation  140 , the MIMO wireless sensor networks communication transceiver system  100  is able to transmit the data rate with an enhancement of a longer range. Moreover, the present invention can simultaneously exploit temporal and spatial diversity for wireless sensor networks communication, thereby enabling spatially distributed sensor node networks into efficient, robust, reliability reliable, and secure wireless sensor networks communication. 
   Different sensor nodes in the MIMO sensor networks communication may be responsible for different levels of throughput and fidelity depending on a particular assigned task. In some cases, some wireless sensor nodes of the MIMO sensor networks communication may have to provide several transmissions within a short-time interval while other wireless sensor nodes may only transmit at irregular intervals or even not at all. Thus, the MIMO sensor networks communication  100  as shown in  FIG. 1  is also used to determine and continually reassess resource allocations so that accommodations of such versatility can be achieved in performance for wireless sensor networks communication. 
   The present invention of the MIMO sensor networks communication transceiver system  100  simultaneously utilizes multiple antennas on both transmitter and receiver by processing signal samples both in space and time. In the MIMO sensor receiver, space-time processing can increase array gain, spatial and temporal diversity and reduce CCI and ISI. In MIMO sensor transmitter, the spatial dimension can enhance array gain, improve diversity, and reduce generation of CCI and ISI. Thus, the present invention of the MIMO sensor networks communication transceiver system  100  mainly trends to use temporal signal processing. This is because use of the spatial-temporal signal processing can improve average signal power, mitigate fading, and reduce CCI and ISI, thereby significantly improving the capacity, coverage, and quality of wireless seamless sensor networks communication. In addition, dual-transmit diversity can boost the data rate not only on uplink channel but also on downlink channel, which allows the sensor basestation to control sensor nodes. As a result, these wireless sensor node networks become as smart sensors since the sensor nodes can be fully controlled by the MIMO sensor basestation in addition to self-control on the sensor nodes. 
   The main task of the MIMO wireless sensor networks communication system  100  is to detect events, perform quick local data processing, and then transmit the information data over the MIMO wireless communication channels. 
   MIMO Sensor Node and Transceiver Architecture 
     FIG. 2  is a block diagram  200  of showing the MIMO sensor node and transceiver  110  according to some embodiments. The MIMO sensor node and transceiver  110  includes a sensor array unit  210 , an A/D converter unit  220 , a signal processing and data computing unit  230 , MIMO transceiver  240 , a power unit  250  coupled with a power generator  260 , and a memory bank  270 . The sensor array unit  210  contains M sensor nodes in parallel to form an array. Each of these sensors is a multimode sensor device, which can be turned to sensor different input signals. The sensor can be one of electronic, optical, chemical, nuclear fusion, gas/liquid, or any combination sensing that made by using properties of integrated electrical, optical, piezoelectric, and even chemical materials, and so on. The sensor array unit  210  is coupled to the A/D converter unit  220 . The A/D converter unit  220  can have one or several A/D converters in a parallel form to convert the input analog signals based on the observed phenomenon into digital signals and then feeds into the signal processing and data computing unit  230 . The A/D converter unit  220  is also connected to the memory bank  270 , which serves as a pool memory storage in the MIMO sensor node and transceiver. The signal-processing and data computing unit  230 , which is coupled to the memory bank  270  and the MIMO transceiver  240 , manages the procedures that make the sensor node to collaborate with the other sensor nodes and move the sensor node with the knowledge of location in a high accuracy when it is required to carry out the assigned sensing tasks. In addition, the signal processing and data computing unit  230  performs the signal processing based on the collected data to provide surveillance, reconnaissance, target identification, registration and disposition, or anything else along those lines and then passes the useful data information into the MIMO transceiver  240 . That is, instead of sending the raw data to the MIMO sensor basestation  140  (see in  FIG. 1 ) responsible for the fusion, the signal processing and data computing unit  230  use its processing abilities to locally carry out simple computations and provides only the required and partially processing data for transmitting. The MIMO transceiver  240  is expected to reliably and securely transmit its data to the MIMO sensor basestation  140  for further analysis, pattern recognition, coordination, and processing during various time intervals. The MIMO sensor node and transceiver system  200  is supported by the power unit  250 , which is coupled to the power generator  260 . The power generator  260  may be a set of solar cells, low-power DC source, or any combinations. The power unit  250  is needed to support three major domains: sensing, signal and data processing and communication. 
   Referring to  FIG. 3  is a detailed block diagram  300  of showing a MIMO transceiver  240  according to some embodiments. A sensing data sequence stream  310  is coupled to a forward error correction (FEC), interleaver and spreading  320 . The FEC, interleaver and spreading  320  is connected with a space-time encoding  330  to produce space-time signal sequences in parallel form and feeds them into a modulation and radio frequency transmitter  340 . The modulation and radio frequency transmitter  340  performs modulation and carrier-based radio signals into air via multiple antennas of  350   a ,  350   b  to  350   k.    
   Referring to  FIG. 4  is a detailed block diagram  400  of showing the FEC, interleaver and spreading  320  according to some embodiments. A convolution encoder  410  that is used to encode the sensor information data is coupled to an interleaver  420 . The output of the convolution encoder  410  is interleaved by using the interleaver  420 . Then, the output data of the interleaver  420  then feeds into a pseudorandom spreader  430 . Using the output of the interleaver  420  with a long pseudorandom sequence, which is generated by using a pseudorandom sequence generator  440 , uses the pseudorandom spreader  430  to perform scrambler. A sensor node mask code  450  is coupled to the pseudorandom sequence generator  440 . The sensor node mask code  450  produces a unique mask sequence for the pseudorandom sequence generator  440 . As a result, the long pseudorandom sequence, which is generated by the pseudorandom sequence generator  440 , is also a unique sequence for the sensor node. In other words, a self-correlation of the long pseudorandom sequence is approximately equal to 1 while a correlation between the long pseudorandom sequence and other long pseudorandom sequences of other sensor nodes is close to 0. 
   Referring to  FIG. 5  is a detailed block diagram  500  of showing the space-time encoding  330  of the MIMO sensor node and transceiver according to some embodiments. A counterclockwise multirate switch unit  510  contains a switch  512  that rotates in a counterclockwise direction from the position of “k” to the position of “a” at each of chip rate speed. The counterclockwise multirate switch unit  510  is used to perform down sampling processing and to divide a LN-length chip sequence of the input signal with a MN Mcps into N parallel sequences of a L-length chip with a M Megachips per second (Mcps). The switch  512  of the counterclockwise multirate switch unit  510  rotationally connects to one of N sensor channel memory banks from  520   a  to  520   k  at each of chip rate speed. All of the sensor channel memory banks from  520   a  to  520   k  have a size of L in memory. The chip rate of the data in each of the sensor channel memory banks from  520   a  to  520   k  is then M Mcps. The sensor channel memory banks from  520   a  to  520   k  are coupled to N spreaders from  530   a  to  530   k  in parallel. The N spreaders from  530   a  to  530   k  are used to spread the output sequences of the N sensor channel memory banks from  520   a  to  520   k  with N orthogonal sequences generated by an orthogonal sequence generator  560 . The each of N orthogonal sequences has MN Mcps. Thus, the output sequences of the N spreaders from  530   a  to  530   k  also have the chip date with MN Mcps and are all orthogonal each other. The N spreaders from  530   a  to  530   k  are coupled to a dual-mode switch unit  540 . The dual-mode switch unit  540  is used to form two functions either MIMO mode or single-input multiple-output (SIMO) mode. When switches of  540   a ,  540   b , . . . ,  540   k  are respectively connected to the positions of a 1 , b 1 , . . . , k 1 , the dual-mode switch unit  540  is in the MIMO mode. The paralleled output sequences of the N spreaders from  530   a  to  530   k  directly feed into a transmitter. When switches of  540   a ,  540   b , . . . ,  540   k  are respectively connected to the positions of a 2 , b 2 , . . . , k 2 , the dual-mode switch unit  540  is in the SIMO mode. In this case, the dual-mode switch unit  540  connects to a block sum unit  570 , which performs a block summation for all of the output sequences from the N spreaders. The block sum unit  570  is coupled to a serial-to-parallel (S/P) unit  580  that is used to generate N parallel chip sequences for the transmitter. 
   MIMO Sensor Basestation Architecture 
     FIG. 6  is a detailed block diagram  600  of showing the MIMO sensor basestation transceiver  140  according to some embodiments. A K multiple antenna receiver from  610   a  to  610   k  are connected with a demodulation and radio frequency receiver  620 . The demodulation and radio frequency receiver  620  produces K signals in parallel and feed them into a space-time processor and decoding  630 . At same time, the demodulation and radio frequency receiver  620  also passes K paralleled signals into a MIMO channel estimate  660 . The MIMO channel estimate  660  is used to identify MIMO channel characteristics by using either a training sequence or a blind estimate method. The space-time processor and decoding  630  is used to decode the MIMO signal into one single signal and then feeds it into a space-time rake processor  640  and the MIMO channel estimate  660 . The MIMO channel estimate  660  provides the channel information for the space-time processor and decoding  630  and the space-time Rake processor  640 . The space-time Rake processor  640  performs correlation, weighting, and coherent combination of the input signal and produces an output signal of the interest. A pseudorandom sequence generator  670  produces a unique pseudorandom sequence based on the sensor node information and passes it into the space-time Rake processor  640 . The space-time Rake processor  640  is also coupled to a deinterleaver and FEC decoding  650 , which is used to do deinterleaver and perform Viterbi processing to decode the information bits of the sensing node data. 
   Referring to  FIG. 7  is a detailed block diagram  700  of showing the space-time processor and decoding  630  of the MIMO sensor basestation transceiver according to some embodiments. The K paralleled inputs are passed into a space-time matrix equalizer  710 , which is a minimum mean-square error (MMSE) equalizer. The space-time matrix equalizer  710  is used to cancel co-channel interference (CCI) in the spatial domain and ISI either in the space domain or in the time domain depending on where it can be done more efficiently. The outputs of the space-time matrix equalizer  710  are parallel despread with K orthogonal sequences generated by an orthogonal sequence generator  740  by using K despreaders from  720   a  to  720   k . The despread K sequences are then fed into K receiver channel memory banks from  730   a  to  730   k . The K receiver channel memory banks for  730   a  to  730   k  are coupled to a clockwise switch unit  750 . The clockwise switch unit  750  produces a single signal sequence from the outputs of K receiver channel memory banks  730   a  to  730   k  by rotating a switch  752  at chip rate speed. This clockwise switch unit  750  is equivalent to perform an up-sampling processing. 
   Power Saving Operation for MIMO Sensor Nodes 
   The space-time sensor node that is a microelectronic device usually has a limited power supply. In some cases, replacement of power resource may be impossible. Thus, the lifetime of the space-time sensor node is depended on a battery lifetime. The malfunctioning of several space-time sensor nodes may cause significant topological changes so that rerouting of packets and reorganization of the sensor networks is needed. Therefore, power conservation and power management is important in the MIMO sensor node networks communication. 
   The present invention of the space-time sensor nodes has a power saving modes during operation. The power saving modes in the space-time sensor nodes includes: (1) full operation mode; (2) sleep mode; (3) wake-up mode, and (4) partial operation mode. In the full operation mode, the space-time sensor node performs entire operation including sensing, data processing and control, and transmitting and receiving. In the sleep mode, the space-time sensor node is in idle. In the wake-up mode, the space-time sensor node randomly wakes up during setup and turns space-time radio off while in inactive. Furthermore, when the space-time sensor node is in the partial operation mode, the space-time sensor node may only operate sensing and simple processing. If the observed data is important, then the space-time sensor node is switched to the full operation mode. 
   While the present inventions have been described with respect to a limited number of embodiments, those skilled in the art will appreciate numerous modifications and variations therefrom. It is intended that the appended claims cover all such modifications and variations as fall within the true spirit and scope of these present inventions.