Linear feedback rate bounds for regressive channels (Corresp.)

This article presents new tighter upper bounds on the rate of Gaussian autoregressive channels with linear feedback. The separation between the upper and lower bounds is small. We havefrac{1}{2} ln left( 1 + rho left( 1+ sum_{k=1}^{m} alpha_{k} x^{- k} right)^{2} right) leq C_{L} leq frac{1}{2} ln left( 1+ rho left( 1+ sum_{k = 1}^{m} alpha_{k} / sqrt{1 + rho} right)^{2} right), mbox{all rho}, whererho = P/N_{0}W, alpha_{l}, cdots, alpha_{m}are regression coefficients,Pis power,Wis bandwidth,N_{0}is the one-sided innovation spectrum, andxis a root of the polynomial(X^{2} - 1)x^{2m} - rho left( x^{m} + sum^{m}_{k=1} alpha_{k} x^{m - k} right)^{2} = 0.It is conjectured that the lower bound is the feedback capacity.     

Temperature dependence of MOSFET characteristics in weak inversion

A knowledge of the MOSFET operating in weak inversion is important for circuits with low leakage specifications. This paper discusses the effect of temperature on the MOSFET in weak inversion. The reciprocal slopenof the log IDSversus VGSrelationship between source-drain current IDSand gate bias VGSmay be given byfrac{1}{(n - 1 - gamma)^{2}} = frac{2Cmin{ox}max{2}}{qepsilon_{s}N_{B}} [frac{3}{4} frac{E_{g^{0}}{q} - (frac{3}{2}alpha + frac{k}{q})T]withalpha equiv (k/q)(38.2 - ln N_{B} + (3/2) ln T)and γ ≡C_{ss}/C_{ox}, where Coxis the oxide capacitance per unit area, Cssthe surface states capacitance per unit area,qthe electronic charge, εsthe permittivity of silicon, NBthe bulk doping concentration,kthe Boltzmann's constant,Tthe absolute temperature, andE_{g0}the extrapolated value of the energy gap of lightly doped silicon atT = 0K. This theoretical formula was in good agreement with experimental results in a temperature range of interest.     

A theorem on the entropy of certain binary sequences and applications--I

In this, the first part of a two-part paper, we establish a theorem concerning the entropy of a certain sequence of binary random variables. In the sequel we will apply this result to the solution of three problems in multi-user communication, two of which have been open for some time. Specifically we show the following. LetXandYbe binary randomn-vectors, which are the input and output, respectively, of a binary symmetric channel with "crossover" probabilityp_0. LetH{X}andH{ Y}be the entropies ofXandY, respectively. Then begin{equation} begin{split} frac{1}{n} H{X} geq h(alpha_0), qquad 0 leq alpha_0 &leq 1, Rightarrow \ qquad qquad &qquad frac{1}{n}H{Y} geq h(alpha_0(1 - p_0) + (1 - alpha_0)p_0) end{split} end{equation} whereh(lambda) = -lambda log lambda - (1 - lambda) log(l - lambda), 0 leq lambda leq 1.     

Weight enumerator for second-order Reed-Muller codes

In this paper, we establish the following result. Theorem:A_i, the number of codewords of weightiin the second-order binary Reed-Muller code of length2^mis given byA_i = 0unlessi = 2^{m-1}or2^{m-1} pm 2^{m-l-j}, for somej, 0 leq j leq [m/2], A_0 = A_{2^m} = 1, and begin{equation} begin{split} A_{2^{m-1} pm 2^{m-1-j}} = 2^{j(j+1)} &{frac{(2^m - 1) (2^{m-1} - 1 )}{4-1} } \ .&{frac{(2^{m-2} - 1)(2^{m-3} -1)}{4^2 - 1} } cdots \ .&{frac{(2^{m-2j+2} -1)(2^{m-2j+1} -1)}{4^j -1} } , \ & 1 leq j leq [m/2] \ end{split} end{equation} begin{equation} A_{2^{m-1}} = 2 { 2^{m(m+1)/2} - sum_{j=0}^{[m/2]} A_{2^{m-1} - 2^{m-1-j}} }. end{equation}     

Bounds for truncation error in sampling expansions of band-limited signals

Forf(t)a real-valued signal band-limited to- pi r leq omega leq pi r (0 < r < 1)and represented by its Fourier integral, upper bounds are established for the magnitude of the truncation error whenf(t)is approximated at a generic timetby an appropriate selection ofN_{1} + N_{2} + 1terms from its Shannon sampling series expansion, the latter expansion being associated with the full band[-pi, pi]and thus involving samples offtaken at the integer points. Results are presented for two cases: 1) the Fourier transformF(omega)is such that|F(omega)|^{2}is integrable on[-pi, pi r](finite energy case), and 2)|F(omega)|is integrable on[-pi r, pi r]. In case 1) it is shown that the truncation error magnitude is bounded above byg(r, t) cdot sqrt{E} cdot left( frac{1}{N_{1}} + frac{1}{N_{2}} right)whereEdenotes the signal energy andgis independent ofN_{1}, N_{2}and the particular band-limited signal being approximated. Correspondingly, in case 2) the error is bounded above byh(r, t) cdot M cdot left( frac{1}{N_{1}} + frac{1}{N_{2}} right)whereMis the maximum signal amplitude andhis independent ofN_{1}, N_{2}and the signal. These estimates possess the same asymptotic behavior as those exhibited earlier by Yao and Thomas [2], but are derived here using only real variable methods in conjunction with the signal representation. In case 1), the estimate obtained represents a sharpening of the Yao-Thomas bound for values ofrdose to unity.     

Channel waveguides in glass via silver-sodium field-assisted ion exchange

Multimode channel waveguides were formed by field-assisted diffusion of Ag+ ion from vacuum-evaporated Ag films, into a sodium aluminosilicate glass reported to yield high diffusion rates for alkali ions. Two-dimensional index profiles of channel waveguides formed by diffusion from a strip aperture were controlled by means of diffusion time, temperature, and electric field. The diffusion equation for diffusion through a strip aperture in the presence of a one-dimensional electric field was solved. Its solution was in agreement with measured concentration profiles:frac{C(x,y,t)}{C_{0}} = frac{1}{2} { erf (frac{a - x}{2sqrt{Dt}}) + erf (frac{a + x}{2sqrt{Dt}})}.frac{1}{2} { erfc (frac{y - muE_{y}t}{2sqrt{Dt}}) + e^{(yE_{y}/D)} erfc (frac{y + muE_{y}t}{2sqrt{Dt}})}Diffusion coefficients in this aluminosilicate glass were determined to beD =(2.41 times 10^{-13}) (frac{m^{2}}{s})).exp (frac{-3.1 times 10^{4}frac{J}{mol}}{RT})Diffusion coefficients were higher (between 150°C and 300°C) than those of a low-iron soda-lime silicate glass "standard" also studied, for which diffusion coefficients wereD =(3.28 times 10^{-13} (frac{m^{2}}{s})).exp (frac{-3.6 times 10^{4}}{RT} (frac{J}{mol}))This difference in diffusion coefficients is due to the higher activation energy of diffusion in the soda-lime silicate glass. The Gladstone-Dale relation was used to calculate the maximum possible refractive index change via Ag+-Na+ ion-exchange for each type of glass. The maximum index change in the sodium aluminosilicate glass is found to be about 65 percent of that in the soda-lime silicate glass.     

An estimate of the variation of a band-limited process

Upper and lower bounds are established for the mean-square variation of a stationary processX(t)whose power spectrum is bounded byomega_{c}, in terms of its average powerP_{0}and the average powerP_{1}of its derivative. It is shown thatleft( frac{2}{pi} right)^{2} P_{1} tau^{2} leq E {|X(t+tau )-X(t)|^{2}} leq P_{1} tau^{2} leq omega_{c}^{2}P_{0}tau^{2}where the upper bounds are valid for anytauand the lower bound fortau < pi / omega_{c}. These estimates are applied to the mean-square variation of the envelope of a quasi-monochromatic process.     

Writing on dirty paper (Corresp.)

A channel with outputY = X + S + Zis examined, The stateS sim N(0, QI)and the noiseZ sim N(0, NI)are multivariate Gaussian random variables (Iis the identity matrix.). The inputX in R^{n}satisfies the power constraint(l/n) sum_{i=1}^{n}X_{i}^{2} leq P. IfSis unknown to both transmitter and receiver then the capacity isfrac{1}{2} ln (1 + P/( N + Q))nats per channel use. However, if the stateSis known to the encoder, the capacity is shown to beC^{ast} =frac{1}{2} ln (1 + P/N), independent ofQ. This is also the capacity of a standard Gaussian channel with signal-to-noise power ratioP/N. Therefore, the stateSdoes not affect the capacity of the channel, even thoughSis unknown to the receiver. It is shown that the optimal transmitter adapts its signal to the stateSrather than attempting to cancel it.     

Hybrid low autocorrelation sequences (Corresp.)

Skew-symmetric sequences of(2n + 1)terms,a_0,a_1,cdots,a_{2n}, are described for which the "merit factor" begin{equation} F_h = frac{biggl[sum_{i=0}^{2n} mid a_i mid biggr] ^2}{ 2 sum_{k=1}^{2n} biggl[ sum_{i=0}^{2n-k} text{sign} (a_i) cdot a_{i+k} biggl] ^2} end{equation} is unusually high.     

An upper bound for codes for the noisy two-access binary adder channel (Corresp.)

Using earlier methods a combinatorial upper bound is derived for|C|. cdot |D|, where(C,D)is adelta-decodable code pair for the noisy two-access binary adder channel. Asymptotically, this bound reduces toR_{1}=R_{2} leq frac{3}{2} + elog_{2} e - (frac{1}{2} + e) log_{2} (1 + 2e)= frac{1}{2} - e + H(frac{1}{2} - e) - frac{1}{2}H(2e),wheree = lfloor (delta - 1)/2 rfloor /n, n rightarrow inftyandR_{1}resp.R_{2}is the rate of the codeCresp.D.     

A Gaussian channel with slow fading (Corresp.)

An interleaved fading channel whose state is known to the receiver is analyzed. The reliability functionE(R)is obtained for ratesRin the rangeR_c leq R leq C. The capacity is shown to beC = E_A { frac{1}{2} ln (1 + A^2 n)}whereAis a factor describing the fading mechanism anduis the signal-to-noise ratio per dimension.     

Convergence to the rate-distortion function for Gaussian sources

In this paper we derive an expression for the minimum-mean-square error achievable in encodingtsamples of a stationary correlated Gaussian source. It is assumed that the source output is not known exactly but is corrupted by correlated Gaussian noise. The expression is obtained in terms of the covariance matrices of the source and noise sequences. It is shown that ast rightarrow infty, the result agrees with a known asymptotic result, which is expressed in terms of the power spectra of the source and noise. The rate of convergence to the asymptotic results as a function of coding delay is investigated for the case where the source is first-order Markov and the noise is uncorrelated. WithDthe asymptotic minimum-mean-square error andD_tthe minimum-mean-square error achievable in transmittingtsamples, we findmid D_t - D mid leq O((t^{-1} log t) ^ {1/2})when we transmit the noisy source vectors over a noiseless channel andmid D_t - D mid leq O((t^{-1} log t)^ {1/3})when the channel is noisy.     

On the capacity of certain additive non-Gaussian channels

A model of an additive non-Gaussian noise channel with generalized average input energy constraint is considered. The asymptotic channel capacityC_{zeta}(S), for large signal-to-noise ratioS, is found under certain conditions on the entropyH_{ tilde{ zeta}}( zeta)of the measure induced in function space by the noise processzeta, relative to the measure induced bytilde{zeta}, where is a Gaussian process with the same covariance as that ofzeta. IfH_{ tilde{zeta}}( zeta) < inftyand the channel input signal is of dimensionM< infty, thenC_{ zeta}(S)= frac{1}{2}M ln(1 + S/M) + Q_{zeta}( M ) + {o}(1), where0 leq Q_{ zeta}( M ) leq H_{ tilde{ zeta}}( zeta). If the channel input signal is of infinite dimension andH_{ tilde{ zeta}}( zeta) rightarrow 0forS rightarrow infty, thenC_{ zeta}(S) = frac{1}{2}S+{o}(1).     

A bound on lightweight sequences with application to definite decoding (Corresp.)

It is shown that the numberMof binary-valuedn-tuples having fractional weightdeltaor less,0 < delta leq frac{1}{3}, such that no twon-tuples agree in anyLconsecutive positions, is bounded by2^{2LH(delta)+1}. A set ofn-tuples is constructed to show that this bound is not likely to be improved upon by any significant factor. This bound is used to show that the ratiod_{DD}/n_{DD}of definite-decoding minimum distance to definite-decoding constraint length is lower bounded byH^{-l}[frac{1}{6} cdot (1 - R)/ (1+R)]asn_{DD}grows without bound.     

Narrow-band systems and Gaussianity

The approach to Gaussianity of the outputy(t)of a narrow-band systemh(t)is investigated. It is assumed that the inputx(t)is ana-dependent process, in the sense that the random variablesx(t)andx(t + u)are independent foru > a. WithF(y)andG(y)the distribution functions ofy(t)and of a suitable normal process, a realistic boundBon the differenceF(y) -- G(y)is determined, and it is shown thatB rightarrow 0as the bandwidthomega_oof the system tends to zero. In the special case of the shot noise process begin{equation} y(t) = sum_i h(t - t_i) end{equation} it is shown that begin{equation} mid F(y) - G(y) mid < (omega_o/lambda) frac{1}{2} end{equation} wherelambda_iis the average density of the Poisson pointst_i.     

A simple analysis of the stable field profile in the supercritical TEA

An analytical investigation supported by numerical calculations has been performed of the stable field profile in a supercritical diffusion-stabilized n-GaAs transferred electron amplifier (TEA) with ohmic contacts. In the numerical analysis, the field profile is determined by solving the steady-state continuity and Poisson equations. The diffusion-induced short-circuit stability is checked by performing time-domain computer simulations under constant voltage conditions. The analytical analysis based on simplifying assumptions gives the following results in good agreement with the numerical results. 1) A minimum doping level required for stability exists, which is inversely proportional to the field-independent diffusion coefficient assumed in the simple analysis. 2) The dc current is bias independent and below the threshold value, and the current drop ratio increases slowly and almost linearly with the doping level. 3) The domain width normalized to the diode lengthLvaries almost linearly with(V_{B}/V_{T}-1)^{frac{1}{2}}/(n_{0}L)^{frac{1}{2}}where VBis the bias voltage VTis the threshold voltage, and no is the doping level. 4) The peak domain field varies almost linearly with (V_{B}/V_{T}-1)^{frac{1}{2}} (n_{0}L)^{frac{1}{2}}. Those results contribute to the understanding of the highn_{0}L-product switch and the stability of the supercritical TEA.     

Mutual information of the white Gaussian channel with and without feedback

The following model for the white Gaussian channel with or without feedback is considered: begin{equation} Y(t) = int_o ^{t} phi (s, Y_o ^{s} ,m) ds + W(t) end{equation} wheremdenotes the message,Y(t)denotes the channel output at timet,Y_o ^ {t}denotes the sample pathY(theta), 0 leq theta leq t. W(t)is the Brownian motion representing noise, andphi(s, y_o ^ {s} ,m)is the channel input (modulator output). It is shown that, under some general assumptions, the amount of mutual informationI(Y_o ^{T} ,m)between the messagemand the output pathY_o ^ {T}is directly related to the mean-square causal filtering error of estimatingphi (t, Y_o ^{t} ,m)from the received dataY_o ^{T} , 0 leq t leq T. It follows, as a corollary to the result forI(Y_o ^ {T} ,m), that feedback can not increase the capacity of the nonband-limited additive white Gaussian noise channel.     

An improved error bound for equal-strength diversity channels (Corresp.)

An upper bound on the minimum probability of error for an equal-strength diversity channel is simply derived that improves a previously known bound by the factor[4(1 - p)]^(-1),0 leq p leq frac{1}{2}.     

An approximation to the weight distribution of binary primitive BCH codes with designed distances 9 and 11 (Corresp.)

Recently Kasami {em et al.} presented a linear programming approach to the weight distribution of binary linear codes [2]. Their approach to compute upper and lower bounds on the weight distribution of binary primitive BCH codes of length2^{m} - 1withm geq 8and designed distance2t + 1with4 leq t leq 5is improved. From these results, the relative deviation of the number of codewords of weightjleq 2^{m-1}from the binomial distribution2^{-mt} left( stackrel{2^{m}-1}{j} right)is shown to be less than 1 percent for the following cases: (1)t = 4, j geq 2t + 1andm geq 16; (2)t = 4, j geq 2t + 3and10 leq m leq 15; (3)t=4, j geq 2t+5and8 leq m leq 9; (4)t=5,j geq 2t+ 1andm geq 20; (5)t=5, j geq 2t+ 3and12 leq m leq 19; (6)t=5, j geq 2t+ 5and10 leq m leq 11; (7)t=5, j geq 2t + 7andm=9; (8)t= 5, j geq 2t+ 9andm = 8.     

Some integrals involving theQ_Mfunction (Corresp.)

Some integrals are presented that can be expressed in terms of theQ_Mfunction, which is defined as begin{equation} Q_M(a,b) = int_b^{infty} dx x(x/a)^{M-1} exp (- frac{x^2 + a^2}{2}) I_{M-1}(ax), end{equation} whereI_{M-1}is the modified Bessel function of orderM-1. Some integrals of theQ_Mfunction are also evaluated.