USRE45775E1 - Method and system for robust, secure, and high-efficiency voice and packet transmission over ad-hoc, mesh, and MIMO communication networks - Google Patents
Method and system for robust, secure, and high-efficiency voice and packet transmission over ad-hoc, mesh, and MIMO communication networks Download PDFInfo
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- USRE45775E1 USRE45775E1 US14/253,563 US201414253563A USRE45775E US RE45775 E1 USRE45775 E1 US RE45775E1 US 201414253563 A US201414253563 A US 201414253563A US RE45775 E USRE45775 E US RE45775E
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- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/04—TPC
- H04W52/18—TPC being performed according to specific parameters
- H04W52/26—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
- H04W52/265—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the quality of service QoS
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- H—ELECTRICITY
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
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- H04B7/0413—MIMO systems
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- H04L5/0007—Time-frequency the frequencies being orthogonal, e.g. OFDM(A), DMT
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- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Abstract
Description
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- Common, scalable transceiver blocks that can be implemented at individual nodes in the communication network (allowing phased addition of hardware and software without immediately rendering obsolete the previous infrastructure).
- Integration into a signal's waveform structure (“overhead structure”) of overhead bits associated with point-to-point links in the network, e.g., Transmit and Receive Node Addresses (TNA's and RNA's), and then use of the resulting unified waveform structure both to securely identify nodes attempting to communicate with a receiver, and to develop linear combiner weights that can extract those signals from co-channel interference incident on that receiver (including interference from other nodes attempting to communicate with that receiver). This approach thereby eliminates bits needed for transmission of TNA and RNA in headers attached to data packets transmitted over each link in the network, as well as overhead needed for transmission of pilot tones/sequences, training signals, preambles/midambles, Unique Words, etc., typically used to train receivers in the network; thus reducing the transmission overhead and improving information-transmission efficiency.
- Ability to further exploit overhead structure to increase transmit power and data rate, or to allow same-rate communication at reduced power to nodes in the network, thereby regaining link capacity lost by that overhead structure, with the most capacity regained at low receive signal-to-interference-and-noise-ratio (SINR).
- Optional integration of overhead bits associated with multipoint routes in the network, e.g., Source and Destination Node Addresses (SNA's and DNA's) into the waveform structure used for adaptation of the communication transceivers (“overhead structure”), further reducing bits needed for transmission of SNA and DNA in headers attached to data packets transmitted in multihop networks, and allowing the use of macrodiverse relay networks in which data is coherently transmitted over multiple geographically separated nodes in a network.
- Rapid (single packet) node detection/discovery and join/leave algorithms, allowing individual transceivers to enter or exit the network quickly to exchange traffic, update security codes, etc., and to allow rapid and/or ad hoc configuration of the network as users encounter dynamic changes in multipath, fading, or interference.
- Information assurance (IA) measures, e.g., antijamming and antispoofing capability, at the node and network level, including spreading means that defeat denial-of-service measures in which the frequencies and/or time periods containing synchronization and training bits are selectively jammed by an adversary.
- Adaptive power management and cyclic feature reduction at node, link, and network levels, in order to minimize transmitted power and/or detectable features of emitters in the network.
- Extreme low complexity (<200 kcps DSP software operations, <30 Mcps ASIC or FPGA coreware operations) for communications commensurate with VoIP communication, allowing maintenance of a collaborative networking information commensurate with pedestrian networking applications.
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- Distributed Kalman state circulation to enable wide-base-line network geolocation algorithms
- Internode channel measurement and range/timing/carrier offset estimation algorithms used to enable wide-base-line network geolocation algorithms.
- Collaborative interference avoidance methods during transmission and reception operations, e.g., allowing wide-area communications in presence of jammers in military communication systems, or incumbent broadcast emitters in commercial communication systems (e.g., 802.22).
- Collaborative communication over long-range to out-of-theatre nodes, e.g., reachback nodes in military communication networks, or LEO/MEO/GEO satellites in commercial satellite communication networks.
H12(k;n1,n2)=HT 21(k;n2,n1), EQ. 1
Where H12 (k;n1,n2) is the M1(n2)×M2(n1) MIMO transfer function for the data downlinked from
and,
H21(k;n2,n1) is the M2(n2)×M1 (n1) MIMO transfer function for the data uplink from
D12(W,G)=D21(G*,W*) EQ. 2
where (W2,G1) and (W1,G2) represent the receive and transmit weights employed by all nodes in the network during uplink and downlink operations, respectively. If
g2(k,q)∝w2*(k,q) and g1(k,q)∝w1*(k,q)
where {g2(k,q), w1(k,q)} are the linear transmit and receive weights to transmit data d2(k,q) from node n2(q) to node n1(q) over channel k in the downlink, and where {g1(k,q),w2(k,q)} are the linear transmit and receive weights used to transmit data d1(k,q) from node n1(q) back to node n2(q) over equivalent channel k in the uplink; thereby allowing Eq. 1 to be satisfied for such links.
- ACK Acknowledgement
- ADC Analog-to-Digital Conversion
- ADSL Asynchronous Digital Subscriber Line
- AGC Automatic Gain Control
- BS Base Station
- BER Bit Error Rate
- BW Bandwidth
- CBR Committed Bit-Rate service
- CDMA Code Division Multiple Access
- CE&FC RWA Computationally Efficient And Fast-Converging Receive Weight Algorithm
- CMRS Cellular Mobile Radio Systems
- CODEC Encoder-decoder, particularly when used for channel coding
- CPU Central Processing Unit
- CR Channel Reciprocity
- DAC Digital-to-Analog Conversion
- DEMOD Demodulator
- DMT Digital MultiTone,
- DSL Digital Signal Loss
- DMX De-multiplexer
- DOF Degrees of Freedom
- DSP Digital Signal Processing
- EDB Error-Detection Block
- EEPROM Electronically Erasable, Programmable Read Only Memory
- FDD Frequency Division Duplex
- FDMA Frequency Division Multiple Access
- FFT Fast Fourier Transform(s)
- FPGA Freely Programmable Gate Array
- GPS Global Positioning Satellites
- GSM Global System for Mobile Communications
- LEGO Locally Enabled Global Optimization
- LMS Least Mean-Square
- LNA Low Noise Amplifier
- LS Least-Squares (An alternative form can be ‘matrix inversion’)
- MAC Media Access Control
- MGSO Modified Gram-Schmidt Orthogonalization (most popular means for taking QRD)
- MOD Modulator
- MIMO Multiple-Input, Multiple-Output
- MMSE Minimum Mean-Square Error
- MSE Mean-Square Error
- MT Multitone
- MUX Multiplex, Multiplexer
- NACK Negative acknowledgement & request for retransmission
- NAK Negative Acknowledgement
- OFDM Orthogonal Frequency Division Multiplexing
- PAL Programmable Array Logic
- PDA Personal Data Assistant
- PHS Personal Handiphone System
- PHY Physical layer
- PMP Point-to-Multipoint (An alternative form can be ‘broadcast’)
- PSTN Public Switched Telephone Network
- PSK Phase-Shift Key
- π/4 QPSK (pi/4)-Quadrature Phase Shift Key
- π/4 DQPSK (pi/4)-Digital Quadrature Phase Shift Key
- PTP Point-to-Point
- QAM Quadrature Amplitude Modulation
- QoS Quality of Service
- QRD Matric {Q,R} decomposition (see, MGSO)
- RF Radio Frequency
- RTS Request To Send, recipient ready for traffic
- SDMA Spatial Division Multiple Access
- SINR Signal to Noise Ration (An alternative form can be S/N)
- SOVA Soft-Optimized, Viterbi Algorithm
- SU Subscriber Unit
- TCM Trellis-Coded-Modulation
- TCP/IP Transmission Control Protocol/Internet Protocol
- TDMA Time Division Multiple Access
- TDD Time Division Duplex
- T/R Transmit/Receive (also Tx/Rx)
- UBR Uncommitted Bit-Rate (services)
- ZE-UBR Zero-error, Uncommitted Bit-Rate (services)
minΣqπ2(q)=1Tπ2 such that EQ. 5
ΣqεQ(m)log(1+γ(q))≧β(m) EQ. 6
The required feasibility condition, that ΣqεQ(m)π1(q)≦R1(m) is reported to the network, and in the preferred embodiment, reported to a network controller, so that β(m) can be modified as needed to stay within the constraints.
Prt(q,j)=|wH r(q)Hrt(q,j)gt(j)|2, EQ. 7
where Wr(q) is a receiver weight vector for link q, and,
gt(j) is the transmit weight vector for link j.
By unit normalizing the receive and transmit weights with respect to the background interference autocorrelation matrix, the local model can state:
wr H(q)R1
enabling the nodal model to express the SINR equation as:
ρ(δ(γ)(Prt−δ(Prt))<1, EQ. 9
where ρ(M) is the spectral radius of a matrix M,
the non-negative power transfer matrix Prt has qj'th element given in EQ. 7,
δ(γ) is a diagonal matrix whose q'th element is γ(q)
where
is the post beamforming interference energy, and is assumed constant for the adjustment interval for current transmit power values, the node can solve EQ. 3 in closed form using classic water filling arguments based on Lagrange multipliers. A similar equation is established for the downlink.
using the approximation in Eq. 11, which is a water-filling solution similar to that described above for Eq. 3. This solution requires a high-level network optimizer to control the power constraints, R1(q), to drive the network to a max-min solution.
γ(q)=|h2(q)|π1(q)/i2(q) EQ. 15
γ(q)=|h2(q)|π2(q)/i1(q) EQ. 16
f(γ)=1TF1(γ)=1TF2(γ), EQ. 17
L(γ,g,β)=gTγ EQ. 20
ΣqεQ(m)log(1+γ(q))/≧β(m) EQ. 21
g=∇γf(γ0) EQ. 22
γ*=arg minγL(γ,g,β) EQ. 23
γα=γ0+α(γ*−γ0) EQ. 24
π2(q)=γαi1(q)/h(q)2 EQ. 25
π1(q)=γαi2(q)//h(q)2 EQ. 26
{∇γf(β0)}q=i1(q)i2(q)//|h(q)|2. EQ. 27
Lm(γ, g,β)≡ΣqεQ(m)gqγ(q) EQ. 28
ΣqεQ(m)log(1+γ(q))≧β(m) EQ. 29
gq=i1(q)i2(q)//|h(q)|2 EQ. 30
y(n)=hgs(n)+ε(n) EQ. 31
where y(n) is the output of the beamformer at the time sample, h≈wH r(q)H21(q,q)gt(q), whose square modulus is Prt(q,q),
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- wr(q) is the receive weight vector for link q,
- gt(q) is transmit weight vector for link q,
g is the square root of the transmit power πt(q),
s(n) is the transmitted complex symbol at time sample n,
where h is the channel transfer gain,
S*(n) is the conjugate of s(n),
y(n) is the output of the beamformer at the time sample n,
and,
where βq is the achievable bit capacity as a function of the transmit gains π1(q);
and to characterize the inequality
{circumflex over (β)}q(π1(q))≧β EQ. 35
with a linear half-subspace, and then solving the approximation problem with a simple low dimensional linear program.
x2(k,l)≈i2(k,l)+H21(k,l)s1(k,l) EQ. 36
(uplink network channel model)
x1(k,l)≈i1(k,l)+H12(k,l)s2(k,l) EQ. 37
(downlink network channel model)
within frequency-time channel (k,l) (e.g., tone k within OFDM symbol 1) transmitted and received at uplink frequency f21 (k) and time t21(l) and downlink frequency f12(k) and time t12(l), where
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- s1(k,l)=[sT 1(k,l;n1(l)) . . . sT 1(k,l;n1(N1))]T represents the network signal vector transmitted from nodes {n1(p)} within uplink channel (k,l);
- s2(k,l)=[sT 2(k,l;n2(l)) . . . sT 2(k,l;n2(N2))]T represents the network signal vector transmitted from nodes {n2(q)} within uplink channel (k,l);
- x1(k,l)=[xT 1(k,l;n1(l)) . . . xT 1(k,l;n1(N1))]T represents the network signal vector received at nodes {n1(p)} within uplink channel (k,l);
- x2(k,l)=[xT 2(k,l;n2(l)) . . . xT 2(k,l;n2(N2))]T represents the network signal vector received at nodes {n2(q)} within uplink channel (k,l);
- i1(k,l)=[iT 1(k,l;n1(l)) . . . iT 1(k,l;(N1))]T models the network interference vector received at nodes {n1(p)} within downlink channel (k,l);
- i2(k,l)=[iT 2(k,l;n2(l)) . . . iT 2(k,l;n2(N2))]T models the network interference vector received at nodes {n2(q)} within uplink channel (k,l);
- H21(k,l)=[H2(k,l;n2(q),n1(p))] models the channel response between transmit nodes {n1(p)} and receive nodes {n2(q)} within uplink channel (k,l); and
- H21(k,l)=[H12 (k,l;n1(p), n2(q))] models the channel response between transmit nodes {n2(q)} and receive nodes {n1(p)} within downlink channel (k,l);
and ( )T denotes the matrix transpose operation, and where - s1(k,l;n1) represents the M1(n1)×1 node n1 signal vector transmitted over M1(n1) diversity channels (e.g., antenna feeds) within uplink frequency-time channel (k,l);
- s2(k,l;n2) represents the M2(n2)×1 node n2 signal vector transmitted over M2(n2) diversity channels within within downlink frequency-time channel (k,l);
- x1(k,l;n1) represents the node n1 signal vector received over M1(n1) diversity channels within downlink frequency-time channel (k,l);
- x2(k,l;n2) represents the M2(n2)×1 node n2 signal vector received over M2(n2) diversity channels within uplink frequency-time channel (k,l);
- i1(k,l;n1) models the M1(n1)×1 node n1 interference vector received over M1(n1) diversity channels within downlink frequency-time channel (k,l);
- i2 (k,l;n2) models the M2(n2)×1 node n2 interference vector received over M2(n2) diversity channels within uplink frequency-time channel (k,l);
- n21(k,l;n2,n1) models the M2(n2)×M1(n1) channel response matrix between transmit node n1 and receive node n2 diversity channels, within uplink channel (k,l); and
- H12(k,l;n1,n2) models the M1(n1)×M2(n2) channel response matrix between transmit node n2 and receive node n1 diversity channels, within downlink channel (k,l).
In the absence of far-field multipath between individual nodes, n21(k,l;n2,n1) and H12(k,l;n1,n2) can be further approximated by rank/matrices:
H21(k,l;n2,n1)≈λ21(n1,n2)a2(f21(k),t21(l);n1,n2)aT 1(f21(k),t21(l);n2,n1)×exp{−j2π(τ21(n2,n1)f21(k)−ν21(n2,n1)t12(l))}]
H12(k,l;n1,n2)≈λ12(n2,n1)a1(f12(k),t12(l);n2,n1)aT 2(f12(k),t12(l);n1,n2)×exp{−j2π(τ12(n1,n2)f12(k)−ν12(n1,n2)t12(l))}
where - λ21(n2,n1) models the observed uplink pathloss and phase shift between transmit node n1 and receive node n2;
- λ12(n1,n2) models the observed downlink pathloss and phase shift between transmit node n2 and receive node n1;
- τ21(n2,n1) models the observed uplink timing offset (delay) between transmit node n1 and receive node n2;
- τ12 (n1,n2) models the observed downlink timing offset between transmit node n2 and receive node n1;
- ν21(n2,n1) models the observed uplink carrier offset between transmit node n1 and receive node n2;
- ν12 (n1,n2) models the observed downlink carrier offset between transmit node n2 and receive node n1;
- a1(f,t;n2,n1) models the M1(n1)×1 node n1 channel response vector, between node n2 and each diversity channel used at node n1, at frequency f and time t; and a2(f,t;n1,n2) models the M2(n2)×1 node n2 channel response vector, between node n1 and each diversity channel used at node n2, at frequency f and time t.
- In many applications, for example, many airborne and satellite communication networks, channel response vector a1(f,t;n2,n1) can be characterized by the observed (possibly time-varying) azimuth and elevation {θ1(t;n2, n1), φ1(f,t;n2,n1)} of node n2 observed at n1. In other applications, for example, many terrestrial communication systems, a1(f,t;n2,n1) can be characterized as a superposition of direct-path and near-field reflection path channel responses, e.g., due to scatterers in the vicinity of n1, such that each element of al(f,t;n2,n1) can be modeled as a random process, possibly varying over time and frequency. Similar properties hold for a2(f,t;n1, n2).
s1(k,l;n1)=G1(k,l;n1)d1(k,l;n1)
s2(k,l;n1)=G2(k,l;n2)d2(k,l;n2) EQ. 40
where
d1(k,l;n1)=[d1(k,l;n2(1),n1) . . . d1(k,l;n2(N2),n1)]T
represents the vector of complex data symbols transmitted from node n1 and intended for each of nodes {n2(q)}, respectively, within uplink channel (k,l);
d2(k,l;n2)=[d2(k,l;n1(1),n2) . . . d2(k,l;n1(N1),n2)]T
represents the vector of complex data symbols transmitted from node n2 and intended for each of nodes {n1(q)}, respectively, within downlink channel (k,l);
G1(k,l;n1)=[g1(k,l;n2(1),n1) . . . g1(k,l;n2(N2),n1)]
represents the complex distribution weights used to redundantly distribute symbol vector d1(k,l;n1) onto each diversity channel employed at node n1 within uplink channel (k,l); and
G2(k,l;n2)=[g2(k,l;n1(1),n2) . . . g2(k,l;n1(N1),n2)]
represents the complex distribution weights used to redundantly distribute symbol vector d2(k,l;n2) onto each diversity channel employed at node n2 within downlink channel (k,l); (2) reconstructing the data intended for each receive node using the matrix formula
y1(k,l;n1)=WH 1(k,l;n1)x1(k,l;n1)
y2(k,l;n2)=WH 2(k,l;n2)x2(k,l;n2)
where ( )H denotes the conjugate-transpose (Hermitian transpose) operation, and where
y1(k,l;n1)=[y1(k,l;n2(1),n1) . . . y1(k,l;n2(N2),n1)]T
-
- represents the vector of complex data symbols intended for node n1 and transmitted from each of nodes {n2(q)}, respectively, within downlink channel (k,l);
- y2(k,l;n2)=[y2(k,l;n1(1),n2) . . . y2(k,l;n1(N1),n2)]T represents the vector of complex data symbols intended for node n2 and transmitted from each of nodes {n1(p)}, respectively, within uplink channel (k,l);
W1(k,l;n1)=[w1(k,l;n2(1),n1) . . . w1(k,l;n2(N2),n1)] - represents the complex combiner weights used at node n1 to recover symbol symbols {d1(k,l;n2(q),n1)} intended for node n1 and transmitted from nodes {n2(q)} within uplink channel (k,l); and
W2(k,l;n2)=[w2(k,l;n1(1),n2) . . . w2(k,l;n1(N1),n2)] - represents the complex combiner weights used at node n2 to recover symbol symbols {d2(k,l;n1(p),n2)} intended for node n2 and transmitted from nodes {n1(p)} within uplink channel (k,l).
(3) developing combiner weights that {w1 (k,l;n2,n1)} and {w2 (k,l;n1,n2)} that substantively null data intended for recipients during the symbol recovery operation, such that for n1≠n2:
|wH 1(k,l;n2,n1)a1(f12(k),t12(l);n2,n1)|<<|wH 1(k,l;n1,n1)a1(f12(k),t12(l);n1,n1)|EQ. 42
and
|wH 2(k,l;n1,n2)a2(f21(k),t21(l);n1,n2)|<<|wH 2(k,l;n2,n2)a2(f21(k),t21(l);n2,n2)|EQ. 43
(4) developing distribution weights {g1(k,l;n2,n1)} and {g2(k, l;n1,n2)} that perform equivalent substantive nulling operations during transmit signal formation operations;
(5) scaling distribution weights to optimize network capacity and/or power criteria, as appropriate for the specific node topology and application addressed by the network;
(6) removing residual timing and carrier offset remaining after recovery of the intended network data symbols; and
(7) encoding data onto symbol vectors based on the end-to-end SINR obtainable between each transmit and intended recipient node, and decoding that data after symbol recovery operations, using channel coding and decoding methods develop in prior art.
where symbol index l is referenced to the start of the adaptation frame, and where
-
- p01(k) is a pseudorandom, constant modulus uplink “network” or “subnet” pilot that is known and used at each node in a network or subnet;
- p02(k) is a pseudorandom, constant modulus downlink “network” or “subnet” pilot that known and used at each node in the network;
- p21(k;n2) is a pseudorandom, constant modulus uplink “recipient” pilot that is known and used by every node intending to transmit data to node n2 during uplink transmission intervals;
- p12(k;n1) is a pseudorandom, constant modulus downlink “recipient” pilot that is known and used by every node intending to transmit data to node n1 during downlink transmission intervals;
- p11(k;n1)=exp{j2πδ1(n1)k} is a sinusoidal uplink “originator” pilot that is used by node n1 during uplink transmission intervals;
- p22(k;n2)=exp{j2πδ(n2)k} is a sinusoidal downlink “originator” pilot that is used by node n2 during downlink transmission intervals;
d1(k,l;n2,n1)=p1(k;n2,n1)d01(k,l;n2,n1) EQ. 46
d2(k,l;n1,n2)=p2(k;n1,n2)d02(k,l;n1,n2) EQ. 47
where d01(k,l;n2,n1) and d02(k,l;n1,n2) are the uplink and downlink data symbols provided by prior encoding, encryption, symbol randomization, and channel preemphasis stages.
x01(k,l;n1)=c02(k;n1)x1(k,l;n1) EQ. 53
x02(k,l;n2)=c01(k;n2)x2(k,l;n2) EQ. 48
where c02(k,n1)=[p02(k)12(k;n1)]* and c01(k;n2)=[p01(k)p21(k;n2)]* are the derandomizing code sequences.
exp{−j2πΔ(k−k0)/PK}≈1−j2πΔ(k−k0)/PK
This algorithm first estimates Δ, providing an initial sublag estimate of pseudodelay, before estimating the lag position to further accuracy. The resultant algorithm can reduce the padding factor P, and reduces interpolation errors in the receive combination weights. However, it requires estimation of an additional IFFT using a modified FFT window, and is therefore not preferred in applications where DSP complexity is of overriding importance.
where U(m) is a collection of links in a given aggregate set m, k is a transmission mode index, reflecting the fact that a single link may transmit over multiple diversity channels, π1 (k,q) is the transmit power for mode k and link q, γ(k,q) is the post beamforming signal to interference noise ration, and R1(m) is the total allowed transmit power for aggregate set m; by solving first the reverse link power control problem; then treating the forward link problem in an identical fashion, substituting the
The preferred embodiment linearizes this objective function as a function of γ(q) and optimizes it using the formulation in EQ 28, EQ 29 and
For each aggregate set m, the network now attempts to achieve the given capacity objective, β, by (1) optimizing the receive beamformers, using simple MMSE processing, to simultaneously optimize the SINR; (2) based on the individual measured SINR for each q index, attempt to incrementally increase or lower its capacity as needed to match the current target; and (3) step the power by a quantized small step in the appropriate direction. When all aggregate sets have achieved the current target capacity, then the network can either increase the target capacity β, or add additional users (opportunistically or by signal) to exploit the now-known excess capacity. The network controller of the preferred embodiment is computationally extremely simple and requires a very small feedback channel, or portion of the control channel otherwise unused, to accomplish its tasks.
as the largest possible mutual information that can be obtained, as the one to be used to obtain network optimality.
Network parameters: | Default | Index # |
MNA = Number of node addresses (active | Variable | (1.1.01) |
nodes) in the network | ||
MLA = Number of link addresses (active links) | Variable | (1.1.02) |
in the network | ||
MPA = Number of network-layer port addresses | MNA(MNA − 1) | (1.1.03) |
in the network | ||
MRA = Number of network-layer route | Variable | (1.1.04) |
addresses in the network | ||
Network addresses: | Range | |
mNA = Node address (NA) | 1:MNA | (1.1.05) |
mTNA = Transmit node address (TNA) | 1:MNA | (1.1.06) |
mRNA = Receive node address (RNA) | 1:MNA | (1.1.07) |
mSNA = Source node address (SNA) | 1:MNA | (1.1.08) |
mDNA = Destination node address (DNA) | 1:MNA | (1.1.09) |
mLA = Link address (LA) | 1:MLA | (1.1.10) |
mRLA = Return link address (RLA) | 1:MLA | (1.1.11) |
mPA = Network-layer port address (PA) | 1:MPA | (1.1.12) |
mRA = Network-layer route address (RA) | 1:MPA | (1.1.13) |
Network mappings: | |
μNA(mLA) = [mTNA mRNA]connected by link mLA. | (1.1.14) |
Alternate notationμTNA(mLA), μRNA(mLA) can also be used to | |
refer to individual elements ofμNA. | |
TDD wubframe used by link mLA μTNA(mLA) transmits over | (1.1.15) |
μTDD(mLA) = TDD subframe | |
μTDD(mLA)) | |
μLA(mTNA, mRNA) = Address of link connecting TNA mTNA to | (1.1.16) |
RNA mRNA (0 if no LA) | |
μNA(mLA) = [mTNA mRNA] μLA(mRNA, mTNA) = mLA | |
μRLA(mLA) = Return link address (RLA) for link mLA: | (1.1.17) |
μNA(mLA) = [mTNA mRNA] μNA(μRLA(mLA)) = [mRNA mTNA] | |
kTNA(mframe) = Adapt bin used by TNA mTNA (same for all | |
Links emanating from mTNA) over frame mframe. Same for | |
all links emanating from mTNA. | |
Address-independent datalink parameters: | Default | |
Ncodec = Maximum data encoding rate (can be | 8 | (1.2.01) | |
noninteger) | |||
NFHT = Hadamard bins per frame | 256 | (1.2.02) | |
Nembed = Hadamard bins reserved for | 16 | (1.2.04) | |
adaptation (≦NFHT) | |||
Membed = Modulated bins per port | 16 | (1.2.05) | |
(≦Nembed/Nport) | |||
Ndata = Hadamard bins reserved for data | 240 | (1.2.03) | |
(≦NFHT − Nembed) | |||
Mdata = Hadamard bins modulated by data | 240 | (1.2.03a) | |
(≦Ndata) | |||
Nsub = Subcarriers per OFDM symbol | 64 | (1.2.06) | |
Nsub = Modulated subcarriers per OFDM | 52 | (1.2.07) | |
symbol | |||
MQAM = QAM data symbols per physical data | 12,480 | (1.2.08) | |
frame | |||
NOFDM = OFDM symbols per physical data | 312 | (1.2.09) | |
frame | |||
MOFDM = Modulated OFDM symbols per | 256 | (1.2.10) | |
PPDU | |||
NTDD = Data frames (TDD subframes) per | 2 | (1.2.11) | |
TDD frame | |||
TFFT(μs) = Duration of OFDM FFT in | 3.2 | μs | (1.2.12) |
microseconds (μs) | |||
Tsymbol(μs) = Duration of OFDM symbol in μs | 4 | μs | (1.2.13) |
Tprefix(μs) = Duration of OFDM cyclic prefix | 0.8 | μs | (1.2.14) |
(guard interval) in μs | |||
TPPDU(μs) = Duration of data PPDU in μs | 1,024 | μs | (1.2.15) |
Tframe(μs) = Duration of data frame in μs | 1,250 | μs | (1.2.16) |
TTxRx(μs) = Duration of TxRx turnaround time | 2 | μs | (1.2.17) |
in μs | |||
TIFS(μs) = Duration of interframe space (guard | 226 | μs | (1.2.18) |
time interval) in μs, inclusive of TTxRx | |||
TTDD(μs) = Duration of OFDM cyclic prefix | 2,500 | μs | (1.2.19) |
(guard interval) μs | |||
fsub(MHz) = Subcarrier spacing in MHz | 0.3125 | MHz | (1.2.20) |
(OFDM LPHY) | |||
Wactive(MHz) = Active bandwidth of signal in | 16.25 | MHz | (1.2.21) |
MHz | |||
Node-address dependent datalink parameters: | Default | |
Nant = Antennas available at node | Variable | (1.2.22) |
Mant = Antennas used at node (≦Nant) | Variable | (1.2.23) |
Nport = Physical ports supportable at node | Variable | (1.2.24) |
(≦Nant) | ||
Mport = Physical ports used at node (≦Nport) | Variable | (1.2.25) |
Link-address dependent datalink parameters: | Default | |
Mcodec = Codec rate employed on link | Variable | (1.2.26) |
(0 no data transported) | ||
Mbit = Bits/frame Tx'd over the link | Variable | (1.2.27) |
(Mbit * Mcodec), 0 none | ||
Node-address independent datalink indices: | Range | |
nFHT = Physical FHT input bin index | 1:NFHT | (1.2.28) |
mFHT = Logical FHT input bin index | 1:MFHT | (1.2.29) |
mdata = Logical data bin index | 1:Mdata | (1.2.30) |
Membed = Logical adaptation bin index | 1:Membed | (1.2.31) |
nsub = Physical subcarrier index | 1:Nsub | (1.2.32) |
msub = Logical subcarrier index | 1:Msub | (1.2.33) |
mQAM = Logical QAM data index | 1:MQAM | (1.2.34) |
nOFDM = Physical OFDM symbol index | 1:NOFDM | (1.2.35) |
mOFDM = Logical OFDM symbol index | 1:MOFDM | (1.2.36) |
nTDD = TDD subframe index (TDD | 1:NTDD | (1.2.37) |
instantiations) | ||
nframe = Data frame index (ignores TDD | — | (1.2.38) |
framing) | ||
Node-address dependent datalink indices: | Range | |
nant = Physical antenna index | 1:Nant | (1.2.39) |
mant = Logical antenna index | 1:Mant | (1.2.40) |
nport = Physical port index | 1:Nport | (1.2.41) |
mport = Logical port index | 1:Mport | (1.2.42) |
mframe = Logical frame index, shared by | ≧0 | (1.2.43) |
consecutive node receive and transmit frames | ||
Link-address dependent datalink indices: | Range | |
mbit = Logical data bit (codec input) index | 1:Mbit | (1.2.44) |
Datalink manppings: | ||
vembed(membed) = Physical Hadamard bin modulated by logical | (1.2.45) |
transmit pilot bin membed | |
vdata(mdata) = Physical Hadamard bin modulated by logical data | (1.2.46) |
bin mdata | |
vsub(msub) = Physical subcarrier modulated by logical subcarrier | (1.2.47) |
msub | |
fsub(msub) = Physical baseband link frequency of logical | (1.2.48) |
subcarrier msub | |
vframe(mframe, mTDD) = Physical frame carrying PPDU with frame | (1.2.49) |
index mframe, TDD subframe index mframe. | |
μport(mLA) = Logical transmit or receive port (as appropriate) | (1.2.50) |
providing data for link address mLA. By convention, the same | |
logical port is used on the return path, mport(mLA) = vport(mRLA), | |
mRLA= μRLA(mLA). | |
μLA(mport) = LA serviced by port mport. Inverse of μport(mLA). | (1.2.51) |
Data and Parameter Arrays: |
Dimensions | |||
Transmit data arrays: |
BTNA(mframe) = | Transmitted bits transmitted, frame mframe, | Mbit × Mport | (1.3.1) |
BTNA(mframe) = [bTNA(1; mframe) . . . | |||
bTNA(Mport; mframe)], | |||
bTNA(mport; mframe) = bits Tx′d from node mTNA over | |||
port mport | |||
mport = μport(mLA), where μTNA(mLA) = mTNA | |||
QTNA(msub, mframe) = | QAM data transmitted, subcarrier msub, frame mframe, | Mdata × Mport | (1.3.2) |
| |||
qTNA(Mdata; msub, mframe) = QAM data Tx′d on | |||
data bin mdata | |||
DTNA(msub, mframe) = | FHT input data, subcarrier msub, frame mframe, | MOFDM × Mport | (1.3.3) |
| |||
CTNA(msub, mframe) = | TRANSEC-scrambled FHT output data, subcarrier | MOFDM × Mport | (1.3.4) |
msub, frame mframe, | |||
| |||
STNA(msub, mframe) = | OFDM modulator input data, subcarrier msub, frame | MOFDM × Mant | (1.3.5) |
mframe, | |||
| |||
Transmit parameter arrays: |
RRNA(msub, mframe) = | RNA TRANSEC code, subcarrier msub, frame mframe; | MOFDM × Mport | (1.3.6) |
row mport = receive code for node mRNA = | |||
μRNA(μLA(mport)) | |||
rRNA(mport; msub, mframe) = | |||
r(msub, mframe; μRNA(μLA(mport))), | |||
GTNA(msub, mframe) = | TNA distribution weights, subcarrier msub, frame | Mant × Mport | (1.3.7) |
mframe. | |||
γRLA(mframe) = | Target return-link SINR's, frame mframe. | 1 × Mport | (1.3.8) |
hTx(msub) = | Transmit subcarrier mask (OFDM LPHY), | Mant × 1 | (1.3.9) |
| |||
where TDAC = 1/fDAC is the (node-specific) DAC | |||
output sample period. | |||
hTRC(msub) = | Transmit-recieve compensation weights, equalizes | Mant × 1 | (1.3.10) |
path differences between the RF switch and the | |||
DAC (transmit path) and ADC (receive path) at each | |||
node in the network. Computed during scheduled | |||
Transmit/receive compensation events. |
Receive data arrays: |
XRNA(msub, mframe) = | OFDM demod output data, subcarrier msub, frame | MOFDM × Mant | (1.3.11) |
mframe. | |||
YRNA(msub, mframe) = | TRANSEC-descrambled FHT output data, | MFHT × Mant | (1.3.12) |
subcarrier msub, frame mframe. | |||
| |||
PRNA(msub, mframe) = | Deembedded pilot data, subcarrier msub, frame | Membed × Mant | (1.3.13) |
mframe, | |||
| |||
ZRNA(msub, mframe) = | Deembedded QAM data, subcarrier msub, frame | Mdata × Mant | (1.3.14) |
mframe. | |||
QRNA(msub, mframe) = | Demodulated QAM data, subcarrier msub, frame | Mdata × Mport | (1.3.15) |
mframe. | |||
BRNA(mframe) = | Decoded bits, frame mframe | Mbit × Mport | (1.3.16) |
Receive parameter arrays: |
rRNA(msub, mframe) = | NA TRANSEC code, subcarrier msub, frame mframe. | MOFDM × 1 | (1.3.17) |
Used at node mRNA during receive operations, and at | |||
nodes attempting to communicate with node mRNA | |||
during their transmit operations | |||
WRNA(msub, mframe) = | Rx combiner weights, subcarrier msub, frame mframe. | Mant × Mport | (1.3.18) |
ARx(msub, mframe) = | Rx spatial signature estimates, subcarrier msub, frame | Mant × Mport | (1.3.19) |
mframe. | |||
γLA(msub, mframe) = | Estimated link SINR's, subcarrier msub, frame mframe. | 1 × Mport | (1.3.20) |
Conceptual parameter arrays (not generated, but referred to in operations): |
tTNA(mframe) = | [Sparse ] NA transmit pilot, subcarrier msub, frame | Membed × 1 | (1.3.21) |
mframe, | |||
tTNA(mframe) = | {square root over (Membed)} e(kTNA(mframe)) | ||
CFHT = | Unitary Walsh transformation matrix | MFHT × MFHT | (1.3.22) |
Sdata = | Shift matrix, maps logical data bins to FHT input | MFHT × Mdata | (1.3.23) |
bins | |||
Spilot = | Shift matrix, maps logical pilot bins to FHT input | MFHT × Mpilot | (1.3.24) |
SFHT = | Shift matrix, maps logical bins to physical FHT | MFHT × MFHT | (1.3.25) |
input bins, | |||
SFHT = [Spilot Sdata] | |||
Upper-PHY Signal Processing Operations:
Transmit Operations
- Step TP1: Separately encode each row of transmitted bits BTNA(mframe) into QAM symbols, and map to subcarriers to form QAM transmit data QTNA(msub,mframe). The bit-to-QAM encoder is not specified here. However, the default encoder will be operations cited in the 802.11a standards specification.
- Step TP2: Embed the transmit pilot, and map pilot & data to FHT input bins
- Step TP3: Embed receive pilot for RNA's communicating with the node.
CTNA(msub,mframe)=RRNA(msub,mframe).*(CFHTDTNA(msub,mframe)) (2.1.3) - Step TP4: Distribute the embedded data over the output antennas.
where “.*” denotes the element-wise multiply operation, and lm is the M×1 all-ones vector.
{GTNA(msub,mframe)},
-
- A retrodirective max-SINR approach that sets {GTNA(msub,mframe)} proportional to the receive weights that maximize signal-to-interference-and-noise ratio (SINR) on the return path, and
- A retrodirective max-SIR approach that sets {GTNA(msub, mframe)} proportional to the receive weights that maximize signal-to-interference ratio (SIR), i.e., that provide hard transmit nulls, on the return path.
The max-SIR approach is recommended for initialization of new links; the max-SINR approach is recommended for steady state operation and tracking. The max-SINR transmit weight adaptation algorithm is described in Section 3.2. The max-SIR transmit weight adaptation algorithm is described in Section 4.2.
Receive Processing Operations
- Step RP1: Remove the receive pilot, and inverse-FHT descrambled data
- Step RP2: Separate pilot & data components
PRNA(msub,mframe)=Spilot TYRNA(msub,mframe) (2.2.2)
XRNA(msub,mframe)=Sdata TYRNA(msub,mframe) (2.2.3) - Steps RA, Detect transmit pilots and estimate their SINR's γLA(msub,mframe) (Sections 3.1, 4.1).
-
- Compute combiner weights {WRNA(msub,mframe)} (Sections 3.1, 4.1).
- Compute distribution weights {GTNA(msub,mframe)} to be used on the return path (Sections 3.2, 4.2).
- Step RP3: Recover the QAM link data:
QRNA(msub,mframe)=ZRNA(msub,mframe)WRNA(msub,mframe) (2.2.4)
Two algorithms are specified here to adapt receive combiner weights {WRNA(msub,mframe)},- A retrodirective max-SINR approach that adapts {WRNA(msub,mframe)} to maximize signal-to-interference-and-noise ratio (SINR) of the received pilot data, and
- A retrodirective max-SIR approach that adapts {WRNA(msub,mframe)} to maximize signal-to-interference ratio (SIR) of the received pilot data, i.e., that provide hard receive nulls to separate the signals of interest to the node.
The max-SIR approach is recommended for initialization of new links; the max-SINR approach is recommended for steady state operation and tracking. The max-SINR transmit weight adaptation algorithm is described in Section 3.2. The max-SIR transmit weight adaptation algorithm is described in Section 4.2.
Max-SINR Adaptation Algorithm
Adaptive Receive Algorithm
Starting with the multiantenna received and deembedded pilot data (referred to as PRNA(msub) or PRNA as appropriate to simplify arguments) received and OFDM-demodulated over logical subcarrier msub and logical frame mframe, perform the following operations
- Step RA1: Compute QRD of PRNA(msub,mframe)
- Step RA2: Detect candidate TNA transmit pilots and spatially whitened adaptation weights
- Step RA3: If spatial signature estimates Aport(msub) are available, where Aport(msub) is the import column of ARNA(msub) (see Step RA6), associate detected transmit pilots with receive ports and link addresses.
- Step RA4: Drop and add ports, based on the port matching statistic cmatch(mdet,mport).
- Step RA5: Assign receive ports and link statistics ηLA(msub) and γLA(msub).
ηLA(mport;msub)=ηdet(mdet(mport);msub) (3.1.22)
γLA(mport;msub)=γdet(mdet(mport);msub) (3.1.23)
u(mport,msub)=udet(mdet(mport);msub) (3.1.24)
U(msub)=[u(1;msub) . . . u(mport;msub)] (3.1.25) - Step RA6: Estimate spatial steering matrices {ARNA(msub, mframe)}.
ARNA(msub,mframe)=CH(msub)U(msub) (3.1.26) - Step RA7: Compute combiner weights {WRNA(msub, mframe)}.
WRNA(msub,mframe)=C(msub)U(msub) (3.1.27)
Adaptive Transmit Algorithm
- Step TA2: Compute distribution weights {GTNA(msub, mframe)}.
GTNA(msub,mframe)=[√{square root over (π(1,msub))}wRNA(1,msub) . . . √{square root over (π(Mport,msub))}wRNA(Mport,msub)] (3.2.3)
The target SINR's can also be derived from rate targets based on performance of the codec's used in the system, or from capacity targets {CRLA(mRLA)} or spectral efficiency targets {cRLA(mRLA)}, via the formula
cRLA(mRLA)=1.63CRLA(mRLA)/Wactive (3.2.4)
γRLA(mRLA)=λgap(2CRLA(mRLA) −1)cRLA(mRLA) (3.2.5)
Where 1.63=1/0.6144 is the inverse efficiency of the airlink, which includes overhead for transmit pilots (0.9375 efficiency), the OFDM cyclic prefix (0.80 efficiency) and TDD framing (0.8192 efficiency), and where λgap is the SNR coding gap of the QAM codec. Target SINR, rate, or capacity can be set at either end of the link, i.e., as a transmitter design goal or as a control parameter passed from the link or network. In the first two cases, this adaptation is referred to here as locally enabled network optimization (LEGO).
and monitoring PRLA(mant) to ensure compliance with conducted power requirements.
- Step RA1: Compute QRD of PRNA(msub,mframe), using (3.1.1)-(3.1.6).
- Step RA2: Detect candidate TNA transmit pilots and spatially-whitened max-SINR adaptation weights using (3.1.7)-(3.1.13).
- Step RA3: If spatial signature estimates ARNA(msub) are available (see Step RA7), associate detected transmit pilots with receive ports and link addresses, using (3.1.14)-(3.1.17).
- Step RA4: Drop and add ports using (3.1.18)-(3.1.21).
- Step RA5: Assign max-SINR whitened transmit/receive weights and link statistics using (3.1.22)-(3.1.25).
- Step RA6: Estimate spatial steering matrices {ARNA(msub, mframe)} using 3.1.26.
- Step RA7: Compute combiner weights {WRNA(msub, mframe)}, using (3.1.27).
- Step RA7.1: Compute null-steering receive weights and SINR's
Adaptive Transmit Algorithm
Starting with the transmit weights WRNA(msub,mframe) given in (4.1.4) and target SINR's γRLA for the return link, perform the following operations.
- Step TA1: Compute ηRLA(mport) using (3.2.1).
- Step Compute power scaling π(mport;msub) using
- TA1.1:
π(mport;msub)=ηRLA(mport)ηLA(mport;msub),(ηLA(mport;msub) given in (3.1.22)) (4.2.1)
- TA1.1:
- Step TA2: Compute combiner weights {GRNA(msub,mframe)} using 3.2.3
The target SINR's can also be derived from rate targets based on performance of the codec's used in the system, or from capacity targets {CRLA(mRLA)} or spectral efficiency targets {cRLA(mRLA)} using (3.2.4)-(3.2.5), and conducted power can be monitored using (3.2.6). In addition, the SINR and SIR estimates given by (3.1.23 and (4.1.3) can be used to detect “overloaded network” conditions where the max-SIR solution is misadjusting significantly from the max-SINR result. While this invention has been described with reference to one or more illustrative embodiments, this description is not to be construed in a limiting sense. Various modifications and combinations of the illustrative embodiments, differing order of the sub-steps (including parallel and partial processing for one or more operations thereof), as well as other embodiments of the invention will be apparent to those skilled in the art upon referencing this disclosure. It is therefore intended this disclosure encompass any combination of the specifics described here and such modifications or embodiments. Furthermore, the scope of this invention includes any combination of the subordinate parts from the different embodiments disclosed in this specification, and is not limited to the specifics of the preferred embodiment or any of the alternative embodiments mentioned above. Individual configurations and embodiments of this invention may contain all, or less than all, of those disclosed in the specification according to the needs and desires of that user. The claims stated herein should further be read as including those elements which are not necessary to the invention yet are in the prior art, particularly that referenced and incorporated herein thereby, and are necessary to the overall function of that particular claim, and should be read as including, to the maximum extent permissible by law, known functional equivalents to the specification's disclosure, even though those functional equivalents are not exhaustively detailed herein or individually claimed below due to the legal preferences for limiting the number of claims and the law's intent to negate any requirement for combinatorial explosion for overly-detailed description and claiming of known and foreseeable alternatives.
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