Invalid constraint: {constant} <= {convex}

I get an error for this code
and I use slack variable
please help me

    variable Q_new(N,2)
    gama0 = P * db2pow(row0) / sigma2;
    expression R(K,1);
for i = 1 :1: K
      for n = 1:1: N
        r = r + a(n,i) * ( (-gama0 * log2(exp(1)))/(H^2 + sum_square_abs(Q(n)-X(i,:)))/...
        (H^2 +  sum_square_abs(Q(n)-X(i,:)) + gama0) *...
        ( sum_square_abs(Q_new(n)-X(i,:))- sum_square_abs(Q(n)-X(i,:)) )...
        + log2(1 + gama0/(H^2+ sum_square_abs(Q(n)-X(i,:)))) );
    R(i) = r;
    expression eta_lb
    maximize eta_lb
    subject to
    for i = 1:K
    eta <= R (i);
    R (i) >= eta
        norms(Q_new(2:N)-Q(1:N-1),2,2) <= Smax^2 ;
        Q_new(1) == Q_new(N);

error is

Error using cvxprob/newcnstr (line 192)
Disciplined convex programming error:
   Invalid constraint: {constant} <= {convex}

Error in  <=  (line 21)
b = newcnstr( evalin( 'caller', 'cvx_problem', '[]' ), x, y, '<=' );

Error in main (line 133)
    eta <= R (i);

Nonlinear equality constraints are non-convex. Your attempt to commit “convex alchemy” by writing a nonlinear equality as two inequalities does not convexify the constraint, because as you have seen, at least one, and in your case, exactly one of the two constraints must be non-convex.

Please read very carefully

and .

if you can get through at least the first 5 chapters of and solve many of the exercises, you will have a strong foundation for using CVX successfully.