 # A numerically huge bound value is specified

## When I solve the optimization problem, I encounter the following problems： Calling Mosek 9.1.9: 280 variables, 70 equality constraints

MOSEK Version 9.1.9 (Build date: 2019-11-21 11:34:40)
Platform: Windows/64-X86

## *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large *** Error(1400): blc is too large Mosek error: MSK_RES_ERR_INFINITE_BOUND (A numerically huge bound value is specified.)

Status: Error
Optimal value (cvx_optval): NaN

Apparently, the magnitude of some of your input data is huge. So huge, that Mosek won’t even attempt to solve the problem.

So you have anything along the lines of x <= 1e20 ? if so, try reducing the bound to something more like 1e4. if that is reached in the optimal solution, you’ll have to figure out what to do.

Perhaps the units can be changed to make numbers more “reasonable”?

I have written in the constraints that the maximum value of the variable to be optimized does not exceed 40. Why is there a problem of too large data?My code is as follows：
function [feasible,nuSolution] = functionFeasibilityProblemP1(L,K,N,beta,Pmax,gamma,SINRconstraint,P0)
% Pmax = 20;
cvx_begin
variable nu(L,K) %Power allocation
expressions object(K,1) daoshuUI(K,1) daoshuDS(K,1) daoshuRminus(K,1) TaylorDS(K,1) TaylorRminus(K,1)

for k=1:K
daoshuUI(k)=Ksum(beta(:,k));
daoshuDS(k)=N
sqrt(P0(:,k))’*sqrt(gamma(:,k))*sum(sqrt(gamma(:,k))./(sqrt(P0(:,k))+eps));
daoshuRminus(k)=-daoshuUI(k)/((sum(P0’*beta(:,k))+1)*log(2));
TaylorDS(k)=log(sum(nu’beta(:,k))+1+N(sqrt(P0(:,k))’*sqrt(gamma(:,k)))^2+daoshuDS(k)*sum(sum(nu-P0)))/log(2);
TaylorRminus(k)=-log(sum(P0’*beta(:,k))+1)/log(2)+daoshuRminus(k)sum(sum(nu-P0));
object(k)=TaylorDS(k)+TaylorRminus(k);
object(k)>=SINRconstraint;
end
maximize sum(object)
subject to
for l = 1:L
nu(l,:)>=0;
sum(nu(l,:)) == Pmax
K/L;
end

cvx_end

You would have to provide a fully reproducible example with all data. The errors you get are generated only when there is actually a bound of the form x\geq +\infty in the problem passed from cvx to Mosek.